Gpt Model Jobs in Usa

Job Title: Sr AI Platform Engineer- AI Platform Engineer (Guardrails, Observability & Evaluation Infrastructure)

Location, Charlotte, NC, USA (3 days onsite)

Role Overview

AI Platform Engineer to design and build the foundational components that power enterprise scale GenAI applications. This includes data guardrails, model safety tooling, observability pipelines, evaluation harnesses, and standardized logging/monitoring frameworks. This role is critical for enabling safe, reliable, and compliant AI development across multiple use cases, teams, and business units. Idea is to create the common platform services that AI team will build upon.

Key Responsibilities

1. Guardrails, Safety & Governance

• Design and implement data guardrail frameworks (pre processing, redaction, PII/PHI filtering, DLP integration, prompt defenses).

• Build "Model Armor" components such as:

o Input validation & sanitization

o Prompt injection defenses

o Harmful content detection & policy enforcement

o Output filtering, fact checking, grounding checks

• Integrate safety tooling (policy engines, classifiers, DLP APIs, safety models).

• Collaborate with Security, Compliance, and Data Privacy teams to ensure frameworks meet enterprise governance requirements.

2. Observability Frameworks

• Build and maintain observability pipelines using tools like Arize AI (tracing, quality metrics, dataset drift/hallucination tracking, embedding monitoring).

• Define and enforce platform wide standards for:

o Tracing LLM calls

o Token usage and cost monitoring

o Latency and reliability metrics

o Prompt/model version tracking

• Provide reusable SDKs or middleware for engineering teams to adopt observability with minimal friction.

3. Logging, Monitoring & Telemetry

• Design standardized LLM-specific logging schemas, including:

o Inputs/outputs

o Model metadata

o Retrieval metadata

o Safety flags

o User context and attribution

• Build monitoring dashboards for performance, cost, anomalies, errors, and safety events.

• Implement alerting and SLOs/SLIs for LLM inference systems.

4. Evaluation Infrastructure

• Architect and maintain evaluation harnesses for GenAI systems, including:

o RAG evaluation (faithfulness, relevance, hallucination risk)

o Summarization/QA evaluation

o Human-in-the-loop review workflows

o Automated eval pipelines integrated into CI/CD

• Support frameworks such as RAGAS, G Eval, rubric scoring, pairwise comparisons, and test case generation.

• Build reusable tooling for teams to write, run, and track model evaluations.

5. Platform Engineering & Reusable Components

• Develop shared libraries, APIs, and services for:

o Prompt management/versioning

o Embedding pipelines and model wrappers

o Retrieval adapters

o Common data loaders and document preprocessing

o Tool/function schemas

• Drive consistency across teams with standards, reference architectures, and best practices.

• Review system designs across use cases to ensure alignment to platform patterns.

6. Collaboration & Enablement

• Partner with AI engineers, product teams, and data scientists to understand cross cutting needs and convert them into reusable platform features.

• Create documentation, onboarding guides, examples, and developer tooling.

• Provide internal training (brown bags, workshops) on guardrails, observability, and evaluation frameworks.

Required Qualifications

Technical Skills

• 5–10+ years software engineering or ML infrastructure experience.

• Strong Python engineering fundamentals (FastAPI, async, typing/Pydantic, testing).

• Experience with model safety/guardrails approaches (prompt injection defense, PII redaction, toxicity filters, policy enforcement).

• Hands on with Arize AI, LangSmith, or similar LLM observability platforms.

• Experience creating evaluation frameworks using RAGAS, G Eval, or custom rubric systems.

• Strong familiarity with vector databases (Pinecone, Weaviate, Milvus), embeddings, and retrieval pipelines.

• Solid understanding of LLM architectures, tokenization, embeddings, context limits, and RAG patterns.

• Experience in cloud (GCP preferred), Kubernetes/GKE, containers, and CI/CD.

• Strong understanding of security, governance, DLP, data privacy, RBAC, and enterprise compliance requirements.

Soft Skills

• Strong documentation and communication skills.

• Ability to influence engineering teams and standardize best practices.

• Comfortable working across multiple stakeholders—platform, security, ML engineering, product.

Nice to Have

• Experience with LangChain/LangGraph or LlamaIndex orchestrations.

• Experience with , Rebuff, Protect AI, or similar LLM security tooling.

• Experience with GCP Vertex AI pipelines, Model Monitoring, and Vector Search.

• Familiarity with knowledge graphs, grounding models, fact checking models.

• Building SDKs or developer frameworks adopted across multiple teams.

• On prem or hybrid AI deployment experience.

About Us:

Astiva Health, Inc., located in Orange, CA is a premier health plan provider specializing in Medicare and HMO services. With a focus on delivering comprehensive care tailored to the needs of our diverse community, we prioritize accessibility, affordability, and quality in all aspects of our services. Join us in our mission to transform healthcare delivery and make a meaningful difference in the lives of our members.

SUMMARY:

We are seeking a skilled and adaptable Junior AI/ML Engineer to join our fast-moving team building impactful AI solutions in healthcare. Our work focuses on extracting and interpreting data from unstructured medical documents, improving clinical coding accuracy, streamlining administrative processes, and enhancing patient outreach.

Projects will evolve rapidly, from fine-tuning large language models (LLMs) on specialized medical PDFs, to optimizing OCR pipelines in Azure, and new challenges emerge regularly. This role suits someone who thrives in ambiguity, enjoys hands-on model development, and wants to directly influence healthcare delivery through applied AI/ML.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following:

• Design, fine-tune, and optimize large language models (LLMs) and multimodal models for healthcare-specific NLP tasks, such as information extraction, classification, and summarization from clinical documents (e.g., medical charts, patient files, scanned forms).
• Develop and improve document understanding pipelines, including fine-tuning OCR / layout-aware models (especially in cloud environments like Azure AI, Azure Foundry) to handle real-world variability in medical forms, handwriting, and scanned PDFs.
• Build and iterate on end-to-end ML solutions that transform unstructured healthcare data into structured, actionable insights
• Collaborate closely with clinicians, product managers, data annotators, and engineers to define problems, curate/annotate datasets, evaluate model performance against clinical and business metrics, and iterate quickly.
• Deploy models into production environments (cloud-based inference, batch processing, or API endpoints) with attention to latency, cost, scalability, and healthcare compliance considerations (HIPAA, data privacy).
• Stay current with advancements in LLMs, vision-language models, efficient fine-tuning techniques (LoRA/QLoRA, PEFT), RAG, multimodal AI, and domain-specific healthcare AI research.
• Contribute to a culture of rapid prototyping, rigorous evaluation, and continuous improvement in a dynamic project landscape where priorities can shift based on new opportunities or stakeholder needs.
• Other duties as assigned

REQUIRED TECHNICAL SKILLS:

• Proficiency in Python and familiarity with common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Experience applying NLP techniques to unstructured text
• Hands-on experience working with LLMs, including:
• Prompt design and iteration
• Using pre-trained models for classification or extraction tasks
• Foundational understanding of model fine-tuning, such as:
• Fine-tuning transformer models or LLMs for classification or information extraction
• Adapting existing training scripts or examples to new datasets
• Familiarity with model evaluation metrics (precision, recall, F1) and basic error analysis
• Experience working with labeled datasets and annotation outputs, including reviewing label quality
• Understanding of common ML problem types, including binary and multi-label classification
• Awareness of model bias, label noise, and false positives, with the ability to discuss tradeoffs and mitigation strategies
• Basic understanding of production ML workflows (versioning, reproducibility, monitoring concepts)

OTHER SKILLS and ABILITIES:

• Hands-on fine-tuning experience with LLMs (e.g., Hugging Face, OpenAI fine-tuning, Azure Foundry), even if limited to small-scale or academic projects
• Exposure to cloud ML platforms (Azure ML, AWS SageMaker, or GCP)
• Familiarity with RAG architectures and retrieval-based grounding
• Experience with NLP libraries (spaCy, Hugging Face Transformers, NLTK)
• Introductory experience with weak supervision or noisy-label learning
• Interest in healthcare or biomedical NLP
• Curiosity about knowledge graphs, ontologies, or structured prediction
• Familiarity with secure data handling practices
• Willingness and ability to learn workflows for sensitive or regulated data (e.g., HIPAA-covered healthcare data), including privacy-aware data handling and secure ML workflows

EXPERIENCE:

• Bachelor’s Degree in related field
• 1–2 years of experience in machine learning, applied NLP, or software engineering
• Demonstrated some experience training or fine-tuning ML models, not just using APIs
• Ability to collaborate with senior engineers and domain experts and incorporate feedback

BENEFITS:

• 401(k)
• Dental Insurance
• Health Insurance
• Life Insurance
• Vision Insurance
• Paid Time Off
• Free catered lunches

HYBRID NORTH CHICAGO IL

PAY: $60-$65/hr

REQUIRED:

• PhD or Master's degree with extensive experience in Quantitative Systems Pharmacology or Systems Biology model development,

Proven scientific track record and practical experience in several of the following areas:

• Statistical modeling
• Modeling with differential equations
• Model-Informed Drug Development (MIDD)
• Quantitative Systems Pharmacology (QSP) models
• Scripting languages (R, Matlab, Python)
• Drug development
• Critical thinking and self-reflective
• Persistent and resilient
• Ability to connect unrelated concept and to generate original or unique ideas
• Fluency in English required, German would be a plus

Job Description:

• Pharmacometrics is concerned with the mathematical and statistical analyses and modeling of biological, pharmacological, and physiological data and processes. It quantifies the various aspects of the (desired and undesired) effects of drugs in the context of disease. The models are based on clinical data, and provide a basis for informing efficient drug development, regulatory decisions, and optimal treatment of patients.

Purpose:

• We are building comprehensive Model-Informed Drug Development (MIDD) capabilities in-house to create reusable platform models across our oncology portfolio. We seek a talented and motivated expert to develop advanced Quantitative Systems Pharmacology (QSP) models in oncology that enable Virtual Population simulations. You will act as a MIDD expert for oncology and integrate this knowledge into Clinical Pharmacology strategy for related development programs.

This means:

• Develop QSP platform models for multiple oncology mechanisms including:
• Immune checkpoint inhibitors (IO/ICI) across colorectal, lung, and ovarian cancers
• Antibody-drug conjugates across lung, ovarian, and colorectal cancers
• T-cell engagers and bispecifics/trispecifics in multiple myeloma
• CAR-T therapies in hematologic malignancies
• Create and optimize Virtual Populations to capture patient heterogeneity and support clinical trial design
• Implement new methods to enhance QSP-driven MIDD, including AI/machine learning augmentation for literature screening, model drafting, and virtual population optimization
• Deliver practical results that inform dose and regimen selection, optimal combinations, therapy duration, and study design for active development programs
• Work as part of a coordinated team under the oversight of a senior pharmacometrician within the PMx Oncology Group

DEPLOY has been retained to find a Reporting & Data Architect Lead combines advanced reporting development with enterprise-level data governance and architectural leadership. In this role, you will own our client's enterprise reporting platform—designing robust Power BI solutions, managing shared data models, and ensuring the reporting environment remains secure, scalable, and high-performing.

You will also own our client's enterprise reporting standards and governance framework, ensuring reporting across all departments is consistent, trusted, and aligned with best practices. This includes defining reporting conventions, reviewing changes, onboarding departmental report creators, and stewarding enterprise reporting assets such as certified datasets and endorsed reports.

At the enterprise level, you will architect our client's data framework—defining how data is structured, named, documented, and shared across ERP, operational, manufacturing, and corporate systems. You will own the enterprise data dictionary, the centralized semantic model, and key architectural decisions around Microsoft Fabric and other data tooling. This role interacts frequently with executives to align data strategy with organizational growth and reporting needs.

Key Responsibilities

Enterprise Reporting (Hands-On Development)

• Build, optimize, and maintain enterprise-grade Power BI reports, dashboards, datasets, and data models.
• Develop and govern shared semantic models and reusable datasets that power enterprise-wide reporting.
• Use Microsoft Fabric, Dataverse, and related ETL/data management tools to shape and integrate reporting data sources.
• Manage dataset refresh schedules, performance tuning, workspace organization, gateway configuration, and reporting system reliability.
• Implement row-level security (RLS), workspace access patterns, and enterprise reporting permissions—Responsible, with the Director of Technology Accountable.
• Manage reporting governance artifacts including certified datasets, endorsed reports, and enterprise workspace standards.
• Support reporting scalability as our client grows (new factories, new business units, new product lines).

Enterprise Reporting Standards & Governance

• Own our client's enterprise reporting standards framework, covering naming conventions, modeling patterns, documentation practices, lifecycle management, visual design standards, and change control.
• Govern reporting development and deployment across the organization to ensure consistency and prevent duplicate or conflicting models.
• Review and approve reporting change requests, data model modifications, and access requests.
• Lead documentation and enablement for departmental report creators through training, guidance, and structured onboarding.
• Provide strategic direction around reporting maturity, sustainability, and enterprise alignment.

Enterprise Data Architecture

• Design and maintain our client's enterprise data architecture framework across ERP, operational, manufacturing, and corporate systems.
• Own the enterprise data dictionary, defining canonical field names, table structures, business definitions, and version control practices.
• Build and govern the centralized semantic model that powers reporting across the company.
• Advise and strongly influence enterprise-level decisions around Microsoft Fabric, data modeling strategy, and long-term architectural direction—and own the work that follows those decisions.
• Collaborate with engineering and system owners to coordinate schema changes, data integrations, and cross-system alignment.

Leadership & Collaboration

• Partner with C-suite and senior leaders to define reporting roadmaps, enterprise priorities, and data strategy.
• Communicate complex architectural concepts in clear, business-friendly terms.
• Lead cross-functional initiatives that require unified data structures or scalable reporting.
• Apply automation (Power Automate, Fabric pipelines) and AI tools to improve reporting efficiency, data quality, and governance workflows.

Ideal Candidate Profile

• Deep hands-on expertise with Power BI, Microsoft Fabric, data modeling, and cloud data platforms.
• Track record of establishing and enforcing enterprise reporting standards and governance.
• Strong architectural intuition: semantic modeling, master data definition, cross-system alignment, and scalable design.
• Able to operate as both an individual contributor and a strategic leader.
• Experience managing reporting governance artifacts (certified datasets, endorsed reports, workspace strategy).
• Comfortable influencing architectural decisions and guiding technical execution.
• Strong command of foundational tools and languages such as:
• DAX
• Power Query / M
• SQL
• Fabric pipelines / ETL tooling
• Experience with automation and AI-assisted analytics workflows.

Purpose

As a foundational member of our AI Center of Excellence, you will serve as the data science lead for enterprise AI initiatives, architecting and deploying AI solutions that make a meaningful impact across our national retail footprint. The Data Scientist Lead will work with other members of the AI COE and business leadership to identify and execute the highest-impact initiatives, own the data science lifecycle, from hypothesis and feature engineering to model validation and performance monitoring; bridging the gap between cutting-edge AI capabilities and practical business applications.

This role requires a rare blend of deep technical mastery and sharp business acumen, to translate complex data into actionable insights and intelligent systems that enhance customer experience, optimize commercial operations, and enable smarter decision-making at scale. The ideal candidate is passionate about retail innovation, thrives in ambiguity, and is energized by the opportunity to shape AI strategy from the ground up.

You’ll Be Successful With

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. Master's degree preferred.
• 5+ years in Data Science or Applied AI roles, preferably in retail or a customer-facing industry.
• Proven track record of moving models from development into production which deliver measurable impact to the business.
• Expert proficiency in Python and SQL. Comfortable with version control.
• Expertise in supervised/unsupervised learning and modern frameworks (e.g. scikit-learn, PyTorch, or TensorFlow).
• Hands-on experience building with LLMs, RAG architectures, prompt engineering, or AI agent development.
• Experience deploying and monitoring models at scale. Familiar with cloud data platforms (e.g. Databricks or Snowflake) and cloud infrastructure (Azure experience a plus).
• You understand how to apply AI to commercial problems such as demand forecasting, customer- and associate- facing applications, personalization, labor optimization, etc.
• The ability to translate "black box" model outputs into clear, actionable insights for business leadership.
• Proven ability to communicate complex technical concepts to non-technical stakeholders and influence decision-making through data-driven storytelling.
• Strong intellectual curiosity with a bias toward action and continuous improvement.
• Demonstrated ability to work autonomously while collaborating effectively within cross-functional teams.

Your Day Consists Of

• Buy vs Build leadership. Evaluate 3rd-party AI platforms and partnerships. Serve as the technical lead in vetting vendor methodologies, guiding the in-house vs external decisioning.
• Partner with business leadership to identify high-value AI opportunities, defining technical specifications and success metrics that align with enterprise strategy.
• Design, develop, and deploy custom machine learning models (impacting merchandising, commercial, labor, digital, etc.) within the Databricks environment.
• Lead experimentation design, including A/B testing and causal inference, to validate model performance and measure true incremental business lift (ROI).
• Collaborate with data engineers on feature development and with AI developers to wrap models into production-grade APIs and applications.
• Partner closely with the Customer Insights team to ensure model outputs are optimized for consumption within Power BI/DAX, turning complex predictions into actionable insights.
• Establish and enforce MLOps standards across the org, including model versioning, automated retraining, and drift monitoring.
• Serve as the primary ML subject matter expert for the broader Data Science & Insights team. Provide active coaching to analytics leaders, empowering them to identify ML-applicable use cases and effectively incorporate predictive outputs into their own functional workstreams.
• Contribute to the enterprise AI governance framework, ensuring ethical AI practices, data privacy compliance, and model transparency.
• Present findings, recommendations, and project updates to leadership and cross-functional partners in clear, compelling formats.
• Be compliant with all appropriate privacy and security protocols.

Working Conditions (travel, hours, environment)

• Limited travel required including air and car travel
• While performing the duties of this job, the employee is occasionally exposed to a warehouse environment and moving vehicles. The noise level in the work environment is typically quiet to moderate.

Physical/Sensory Requirements

Sedentary Work – Ability to exert 10 - 20 pounds of force occasionally, and/or negligible amount of force frequently to lift, carry, push, pull or otherwise move objects. Sedentary work involves sitting most of the time but may involve walking or standing for brief periods of time.

Benefits & Rewards

• Bonus opportunities at every level
• Non-traditional retail hours (we close at 7p!)
• Career advancement opportunities
• Relocation opportunities across the country
• 401k with discretionary company match
• Employee Stock Purchase Plan
• Referral Bonus Program
• 80 hrs. annualized paid vacation (full-time associates)
• 4 paid holidays per year (full-time hourly store associates only)
• 1 paid personal holiday of associate’s choice and Volunteer Time Off program
• Medical, Dental, Vision, Life and other Insurance Plans (subject to eligibility criteria)

Equal Employment Opportunity

Floor & Decor provides equal employment opportunities to all associates and applicants without regard to age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, disability, veteran status, genetic information, ethnicity, citizenship, or any other category protected by law.

This policy applies to all areas of employment, including recruitment, testing, screening, hiring, selection for training, upgrading, transfer, demotion, layoff, discipline, termination, compensation, benefits and all other privileges, terms and conditions of employment. This policy and the law prohibit employment discrimination against any associate or applicant on the basis of any legally protected status outlined above.

Our client is a forward-thinking consultancy at the forefront of technology and innovation, dedicated to empowering organizations to thrive in an ever-evolving digital landscape. Our clients mission is to help businesses harness the power of data and artificial intelligence to drive growth, enhance customer experiences, and optimize operations.

As they enter their next phase of expansion, they are seeking a GenAI Architect to drive cutting-edge AI/ML projects and turn complex data into actionable insights. You’ll thrive in a client-facing, project-based role, leading teams to design, build, and deploy enterprise-scale models across diverse use cases.

Responsibilities

• Lead project teams and act as the technical architect on AI/ML initiatives.
• Analyze large, complex datasets and translate them into impactful insights using ML and AI techniques.
• Build, implement, and deploy models into production environments, leveraging best practices across cloud and on-prem solutions.
• Collaborate with clients to define requirements, architect solutions, and present technical recommendations.
• Coach and mentor junior team members while driving project success.

Experience

• Proven track record building large-scale AI/ML solutions in enterprise or consulting environments.
• 5+ years of hands-on experience in statistical modelling, analytics, and machine learning.
• Advanced academic background (Master’s in Statistics, Math, Computer Science, or related; PhD is a strong plus).
• Expertise in a wide range of ML and AI techniques: regression models, cluster analysis, predictive modeling, neural networks, deep learning, decision trees, ensemble methods, and more.
• Strong programming skills in Python, TensorFlow, PyTorch, Hugging Face Transformers, and other ML frameworks for model development and experimentation.
• Deep understanding of NLP fundamentals, including tokenization, embeddings, language modeling, sequence labeling, and text generation.
• Experience with modern AI tooling: LangChain, vector databases, prompt engineering, and large-scale data embedding.
• Solid knowledge of relational (SQL) and non-relational (NoSQL) databases, and distributed systems like Hadoop and Spark.
• Ability to turn complex datasets into compelling, actionable insights using visualization tools (RShiny, Python, Tableau, Power BI, D3.js, etc.).
• Passion for mentoring and leading teams, fostering growth and knowledge sharing.
• Experience managing data workflows: wrangling, exploring, transforming, and analyzing diverse datasets.
• Familiarity with monitoring model performance, tuning, and ensuring high-quality data.
• Excellent communication skills with the ability to engage stakeholders at both technical and business levels.
• Strong curiosity and thought leadership, staying ahead of AI/ML trends and research.
• Experience deploying ML models into production on cloud platforms such as Google Cloud Platform, Azure, or AWS.

Please note, our client is unable to support visa transfers at this stage and can hire US citizens or Greencard holders.

If you feel you have the required skills, please get in touch with a copy of your CV! Or email me directly at

At Quotacom, we take the security and privacy of your personal data very seriously, any data we hold will be in accordance with data protection legislation. Full details of our privacy notice can be found at

Looking for a Gen AI architect with 15+ years experience and 8+years experience focusing on Model Optimization, Fine-Tuning & Strategic AI in San Francisco, CA.

Role Summary:

You represent the pinnacle of Applied AI engineering. You are not just using APIs; you are optimizing the models themselves. You understand the mathematics behind the attention mechanism, you know how to squeeze performance out of GPUs, and you can customize models for specific domains. You provide the high-level technical vision and handle the most difficult edge cases. .

Key Responsibilities:

Model Fine-Tuning: Implement PEFT (Parameter-Efficient Fine-Tuning), LoRA, and QLoRA to adapt open-source models (Llama 3, Mistral) to specific client domains.

Optimization & Quantization: Perform model quantization to reduce inference costs and latency without sacrificing quality. Manage Dense Vectors and embedding optimizations.

State-of-the-Art Exploration: Continuously research and implement the latest advancements (e.g., State Space Models, Long-Context optimizations) into client deliverables.

Strategic Consulting: Act as a trusted advisor to C-level client executives, defining the "Art of the Possible" and guiding long-term AI roadmaps.

Technical Requirements:

Deep Learning: PyTorch/TensorFlow, Transformers architecture internals, Attention mechanisms.

Model Ops: Serving custom models (vLLM, TGI), GPU memory management, Quantization techniques (GGUF, AWQ).

Advanced Data: Training data curation, synthetic data generation, RLHF concepts.

Tech Leadership: Ability to define the technical culture and set standards for the entire FDE organization.

Soft Skills:

Executive communication and ability to influence C‑level leaders.

Thought leadership and industry presence (conferences, playbooks, forums).

Cross‑org leadership and conflict resolution.

Ability to define long‑term AI vision and cultural standards.

Strategic decision‑making balancing cost, risk, and performance.

Job Description

This position offers a unique opportunity to work on advanced projects at the intersection of AI, machine learning, computer vision, and multimodal learning, focusing on advancing the Large Language Models (LLMs). The successful candidate will work on pioneering research projects that push the boundaries of what AI can achieve, particularly in the domain of multimodal learning. You will have the opportunity to develop innovative algorithms and models that integrate multiple data modalities, collaborate with industry partners, and contribute to high-impact publications.

Job Responsibilities

1. Research and Innovation:Conduct cutting-edge research in AI, machine learning, and multimodal learning, with a focus on developing Large Language Models (LLMs) that process and generate multimodal data (text, audio, video, images).Explore and implement new algorithms and methodologies to enhance the performance of LLMs in various real-world applications.

2. Model Development and Optimization:Design, build, and fine-tune LLMs and other AI models to address complex challenges in multimodal learning.Develop scalable and efficient architectures for deploying models in real-world environments.

3. Collaboration and Industry Partnerships:Collaborate closely with industry partners to align research with practical applications, ensuring that developed models and solutions address real-world needs.Participate in cross-functional teams to apply research findings to industry-related projects.

4. Publishing and Dissemination:Prepare and publish high-quality research papers in top-tier journals and present findings at leading academic conferences.Contribute to technical reports and documentation for both academic and industry audiences.

5. Mentorship and Lab Contributions:Mentor graduate and undergraduate students in the lab, guiding them in research methods, experimental design, and technical skills. Contribute to the overall success of the lab by collaborating on ongoing projects and assisting with grant proposals and reports.

Minimum Qualification

Ph.D. from an accredited institution in Computer Science, Electrical and Computer Engineering, or a related field with a focus on AI, NLP (natural language processing), machine learning, or data science.

Preferred Qualifications

Expertise in Deep Learning and LLMs(Large Language Models): Knowledge in building applications and fine-tuning models like Llama 3, Gemma, Mistral AI, and others.
Multimodal Learning Experience: Demonstrated experience in integrating and processing multiple data modalities (text, audio, video, images) using AI/ML techniques.
Programming Proficiency: Strong programming skills in Python, with experience in deep learning frameworks such as TensorFlow, PyTorch, and associated libraries.
Research Excellence: Proven track record of publications in high-impact journals and conferences in relevant fields.
Collaborative Mindset: Ability to work effectively in a multidisciplinary team, with strong communication and leadership skills.

Department

Work Schedule

Type of Appointment

Expected Salary

Equal Employment Opportunity Statement:

The University of Central Florida is an Equal Opportunity/Affirmative Action Employer including Disabled/Vets. Click on UCF's Equal Opportunity Statement to view the President's Statement.

The UCF affirmative action plans for qualified individuals with disabilities and protected Veterans are available for inspection in the Office of Institutional Equity, Monday through Friday, from 9:00 a.m. to 5:00 p.m., upon request.

As a Florida public university, UCF makes all application materials and selection procedures available to the public upon request.

The University of Central Florida is proud to be a smoke-free campus and an E-Verify employer.

The Opportunity

The Institute of Simulation and Training (IST) at the University of Central Florida (UCF) is seeking applicants for a full-time, 12-month, non-tenure earning, digital asset and engineer-oriented, research position.This is a full-time Contract and Grants (C&G)-based faculty position to support ongoing federally sponsored research in a long-standing and agile R&D lab. For information about the Institute for Simulation and Training and the Orlando area, see .

We are searching for an Assistant In Digital Asset Research and Production Engineer with expertise in computer visualization, 3D modeling, and immersive technologies to support the design, development, and implementation of next-generation visual simulations and intelligent training systems. The successful candidate will join a multidisciplinary team conducting applied research in simulation-based training, modeling, and opportunity-based training systems.

This position requires an experienced researcher who will work both independently and as a team member to design, develop, modify, test, document, and maintain simulation software products.

Key Responsibilities

• 
  

• Design, develop, and implement 3D environments, frameworks, and prototypes for high-fidelity visual simulations and applications.

  
  

• Apply 3D models, advanced character mesh techniques, and physics-based simulation methods to enhance realism and interactivity in diverse domain systems and applications.

  
  

• Work with interdisciplinary teams including engineers, cognitive scientists, and domain experts to define research objectives, design experiments, and analyze results.

  
  

• Create prototypes and capabilities demonstrators to showcase IST's expertise aligned with trends and opportunities.

  
  

• Design and execute hands-on demonstrations and exhibits at strategic events.

  
  

• Perform data collection in the form of LiDAR, photogrammetry, and other advanced techniques to evolve advanced terrestrial-based synthetic environments.

  
  

Minimum Qualifications:

A master's degree from an accredited institution in a field related to modeling and simulation and two years of related professional experience or a bachelor's degree from an accredited institution in a field related to modeling and simulation and five years of related professional experience.

Significant experience or education required in at least three of the following areas:

• 
  

• 3D modeling tools such as Adobe Substance, Creator, Blender, or 3D Studio Max

  
  

• AutoDesk software systems

  
  

• Geospatial algorithms

  
  

• 3D game engine modeling formats

  
  

• Character and model rigging using modern game engine approaches (Unity, Unreal)

  
  

• Modern terrain generation software

  
  

Preferred Qualifications:

Experience or education is preferred in any of the following areas:

• 
  

• OpenFlight file format and visual database correlation.

  
  

• NIMA data processing

  
  

• Cartography

  
  

• 3D Model/Character creation for modern game engines.

  
  

• Digital twin creation

  
  

• Data acquisition through ground-based LiDAR-based systems such as Leica or Faro systems

  
  

• Intrinsic game engine API scripting capabilities such as C# and/or Python

  
  

• Familiarity with understanding of producing correlated geospecific terrain

  
  

Additional Application Materials Required:

UCF requires all applications and supporting documents be submitted electronically through the Human Resources employment opportunities website, jobs/. In addition to the online application, interested candidates should upload the following:

• 
  

• A curriculum vitae.

  
  

• A letter of interest describing qualifications for the position, such as research agenda and teaching experience/interest.

  
  

NOTE: Please have all documents ready when applying so they can be simultaneously uploaded. Once the online submission process is finalized, the system does not allow applicants to submit additional documents later.

The selected candidate will be required to submit official transcripts (and, as applicable, U.S. degree equivalency evaluations) documenting the conferral of their qualifying academic credentials.

Questions regarding this search should be directed to: Dean Reed at .

Special Instructions to the Applicants:

Sponsorship for employment-based visas will only be considered under exceptional circumstances and is not guaranteed. Preference will be given to candidates who are currently authorized to work for any employer in the United States.

Position requires U.S citizenship for a University-sponsored application for a security clearance. This position is funded by contract and grant sources and is contingent upon available funding.

Job Close Date:

Open until filled.

Are you ready to unleash YOUR potential?

As a next-generation public research university and Forbes-ranked top employer in Florida, we are a community of thinkers, doers, creators, innovators, healers, and leaders striving to create broader prosperity and help shape a better future. No matter what your role is, when you join Knight Nation, you'll play an integral role at one of the most impactful universities in the country. You'll be met with opportunities to connect and collaborate with talented faculty, staff, and students across 13 colleges and multiple campuses, engaging in impactful work that makes a positive difference. Your time at UCF will provide you with many meaningful opportunities to grow, you'll work alongside talented colleagues on complex projects that will challenge you and help you gain new skills and you'll have countless rewarding experiences that go well beyond a paycheck.

Working at UCF has its perks!UCF offers:

• 
  

• Benefit packages, including Medical, Dental, Vision, Life Insurance, Flexible Spending, and Employee Assistance Program.

  
  

• Paid time off, including annual (12-month faculty) and sick time off and paid holidays.

  
  

• Retirement savings options.

  
  

• Employee discounts, including tickets to many Orlando attractions.

  
  

• Education assistance.

  
  

• Flexible work environment.

  
  

• And more...For more benefits information, view the UCF Employee Benefits Guideclick here.

  
  

Unless explicitly stated on the job posting, it is UCF's expectation that an employee of UCF will reside in Florida as of the date the employment begins.

Additional Requirements related to Research Positions:

Pursuant to Florida State Statute 1010.35, prior to offering employment to certain individuals in research-related positions, UCF is required to conduct additional screening. Applicants subject to additional screening include any citizen of a foreign country who is not a permanent resident of the U.S., or who is a citizen or permanent resident but is affiliated with or has had at least 1 year of education, employment, or training in China, Cuba, Iran, Russia, North Korea, Syria, or Venezuela.

The additional screening requirements only apply to research-related positions, including, but not limited to faculty, graduate positions, individuals compensated by research grants or contract funds, post-doctoral positions, undergraduate positions, visiting assistant professors, and visiting research associates.

Department

Work Schedule

Type of Appointment

Expected Salary

As a Florida public university, the University of Central Florida makes all application materials and selection procedures available to the public upon request.

UCF is proud to be a smoke-free campus and an E-Verify employer.

If an accommodation due to a disability is needed to apply for this position, please call or email .

For general application or posting questions, please email .

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime.

This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment.

The ideal candidate combines:

* Strong security engineering and cloud architecture experience

* Deep, current familiarity with modern AI/LLM tooling and practices

* Familiar and can cover basic coding within the AI tooling space (python, others)

* The ability to communicate clearly with senior leadership and influence enterprise-wide strategy

Essential Duties and Responsibilities

Secure AI / ML platforms and workloads

* Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications.

* Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads.

* Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation.

* Partner with data science and MLOps teams to harden:

• Data ingestion and labeling
• Training and fine-tuning pipelines
• Model registries and deployment workflows
• Inference APIs, agents, and integrations

* Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture.

AI use case intake & governance

* Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization.

* Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards.

* Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle.

* Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams.

* Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies.

Monitoring, detection & assurance

* Establish and maintain monitoring and detection for AI-specific threats, such as:

• Prompt injection and jailbreak attempts
• Data exfiltration and sensitive data exposure
• Misuse or abuse of AI tools and agents
• Anomalous model or pipeline behavior

* Integrate AI/ML systems with existing logging, SIEM, and incident response processes.

* Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification.

Strategy, leadership & enablement

* Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk.

* Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments.

* Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress.

* Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems.

Qualifications Expected for Position

• 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems.
• 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems.
• Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries.
• Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring.
• Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred.
• Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption.
• Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership.

Preferred Qualifications:

* Practical experience securing LLM- and genAI-based systems, such as:

• RAG architectures backed by internal data
• AI assistants, copilots, or agents integrated with enterprise tools
• Fine-tuned models and model hosting platforms

* Experience with AI IDE tools

• cursor, windsurfer, others
• Knows the security problems and has practical solutions that balances innovation with innovation.

* Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools).

* Experience with:

• Security for data pipelines, feature stores, and model registries
• Detection engineering or SIEM tuning for AI-related events
• Red-teaming or adversarial testing of AI systems

* Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks).

* Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports.

* Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus.

* Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape.

* High level of integrity and ethical conduct.

This role is a fit if you:

* Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects.

* Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems.

* Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation.

* Can move fluidly between deep technical discussions and concise, executive-level explanations.

This role is not a fit if you:

* Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work.

* Do not actively engage with current AI/LLM tooling, research, and emerging practices.

* "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?"

* "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?"

* "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?"

The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.