Gpt Model Jobs in Usa

Overview

Georgia Tech prides itself on its technological resources, collaborations, high-quality student body, and its commitment to building an outstanding and diverse community of learning, discovery, and creation. We strongly encourage applicants whose values align with our institutional values, as outlined in our Strategic Plan. These values include academic excellence, diversity of thought and experience, inquiry and innovation, collaboration and community, and ethical behavior and stewardship. Georgia Tech has policies to promote a healthy work-life balance and is aware that attracting faculty may require meeting the needs of two careers.

About Georgia Tech

Georgia Tech is a top-ranked public research university situated in the heart of Atlanta, a diverse and vibrant city with numerous economic and cultural strengths. The Institute serves more than 45,000 students through top-ranked undergraduate, graduate, and executive programs in engineering, computing, science, business, design, and liberal arts. Georgia Tech's faculty attracted more than $1.4 billion in research awards this past year in fields ranging from biomedical technology to artificial intelligence, energy, sustainability, semiconductors, neuroscience, and national security. Georgia Tech ranks among the nation's top 20 universities for research and development spending and No. 1 among institutions without a medical school.

Georgia Tech's Mission and Values

Georgia Tech's mission is to develop leaders who advance technology and improve the human condition. The Institute has nine key values that are foundational to everything we do:
1. Students are our top priority.
2. We strive for excellence.
3. We thrive on diversity.
4. We celebrate collaboration.
5. We champion innovation.
6. We safeguard freedom of inquiry and expression.
7. We nurture the well-being of our community.
8. We act ethically.
9. We are responsible stewards.

Over the next decade, Georgia Tech will become an example of inclusive innovation, a leading technological research university of unmatched scale, relentlessly committed to serving the public good; breaking new ground in addressing the biggest local, national, and global challenges and opportunities of our time; making technology broadly accessible; and developing exceptional, principled leaders from all backgrounds ready to produce novel ideas and create solutions with real human impact.

Atlanta, GA

About the School of Electrical and Computer Engineering (ECE) at the Georgia Institute of Technology

The School of Electrical and Computer Engineering (ECE) at the Georgia Institute of Technology is one of the largest producers of electrical engineers and computer engineers in the United States. Almost 2,600 students are enrolled in the School's graduate and undergraduate programs, and in the last academic year, 801 degrees were awarded. All ECE undergraduate and graduate programs are in the top five of the most recent college rankings by U.S. News & World Report.

In addition to the main campus in Atlanta, Georgia, ECE also has permanent operations at Georgia Tech-Lorraine in France. Graduate students who spend at least one semester each at of the Georgia Tech locations (Atlanta, Lorraine, on two continents, North America and Europe) can earn the Georgia Tech Global Engineering Immersion Program (GEIP) Certificate when they receive the Georgia Tech M.S. degree.

Over 110 ECE faculty members are involved in 11 areas of research and education: bioengineering, computer systems and software, digital signal processing, electrical energy, electromagnetics, electronic design and applications, nanotechnology, optics and photonics, systems and controls, telecommunications, and VLSI systems and digital design: and the School is either home to or a key player in almost 20 research centers and consortia.

ECE is key to Georgia Tech's growing reputation as an internationally recognized educational and research and development university. ECE is firmly committed to sustaining excellence in traditional areas of strength and venturing into burgeoning areas of opportunity.

The Signal Lab in the School of Electrical and Computer Engineering at Georgia Tech is seeking a Research Scientist to lead and advance cutting-edge research in Artificial Intelligence. The role will involve laboratory management, project oversight, and business development activities to name a few.

1. Research Leadership in Foundation Models, World Models, and Frontier AI

• Lead and execute advanced research programs in large-scale AI, including foundation model architectures, multimodal representation learning, world models, agentic systems, and self-supervised learning at scale.
• Design and evaluate new training algorithms, model architectures, and scalable pipelines for language, vision, audio, robotics, simulation, and multi-agent environments.
• Develop GPU-, TPU-, and cluster-optimized training frameworks, distributed training systems, and inference-time optimization pipelines for next-generation AI models.
• Publish high-impact papers in top AI/ML venues, release open-source tools, and contribute to Georgia Tech's AI research leadership and national strategic priorities.

2. Lab Management and AI Compute Infrastructure Operations

• Oversee daily operations of the AI research lab, including GPU clusters, high-performance storage, distributed training stacks, and data governance frameworks.
• Manage, maintain, and expand high-performance compute infrastructure: multi-node GPU clusters, distributed data loaders, RL/simulation environments, and model evaluation frameworks.
• Ensure safety, compliance, documentation, model governance, data integrity, and continuous uptime of compute and AI assets.
• Build automated pipelines for model training, experiment reproducibility, dataset generation, benchmarking, and large-scale evaluation.

3. Affiliate Engagement, Business Development, and Partnerships

• Engage, onboard, and support affiliate companies participating in the AI and foundation model research program.
• Serve as a technical liaison for affiliates across AI labs, cloud providers, robotics companies, semiconductor partners, government agencies, and enterprise AI users.
• Define joint research thrusts, scoping documents, datasets, deliverables, evaluation protocols, and IP structures for partner organizations.
• Coordinate demos, campus visits, model showcases, and affiliate meetings to support collaboration and knowledge transfer.

4. Project Management and PhD Mentorship

• Mentor PhD students, postdocs, and research engineers working on foundation models, world models, agentic systems, and large-scale representation learning.
• Manage multi-PI, multi-institution, and affiliate-funded AI research efforts, ensuring timely execution, publications, deliverables, reporting, and stakeholder satisfaction.
• Provide technical direction on model design, dataset creation, training strategies, evaluation, experiment planning, scheduling, milestones, and results dissemination.

Research Scientist/Engineer I

Bachelor's Degree in Electrical Engineering, Physics, or related area.

Research Scientist/Engineer II

• A Master's degree and three (3) years of relevant full-time experience after completion of that degree,
• A Master's degree and five (5) years of relevant full-time experience after completion of a Bachelor's degree, or
• A Doctoral degree.

Senior Research Scientist/Engineer

• A Master's degree and seven (7) years of relevant full-time experience after completion of that degree,
• A Master's degree and nine (9) years of relevant full-time experience after completion of a Bachelor's degree, or
• A Doctoral degree and four (4) years of relevant full-time experience after completion of a Bachelor's degree.

• PhD in Computer Science, Electrical and Computer Engineering, Machine Learning, or a closely related field with emphasis on AI or large-scale model development.
• Strong research record in foundation models, world models, representation learning, multimodal AI, distributed training, or agentic systems.
• Hands-on experience with large-scale model training using GPUs/TPUs, distributed systems, deep learning frameworks (PyTorch, JAX, TensorFlow), and data pipelines.
• Demonstrated experience mentoring students or leading technical AI teams.
• Strong communication and presentation skills for both technical and non-technical audiences.

Linda Dillon, Lucretia Allen or Shalonda Williams at

The University System of Georgia is comprised of our 26 institutions of higher education and learning as well as the System Office. Our USG Statement of Core Values are Integrity, Excellence, Accountability, and Respect. These values serve as the foundation for all that we do as an organization, and each USG community member is responsible for demonstrating and upholding these standards. More details on the USG Statement of Core Values and Code of Conduct are available in USG Board Policy 8.2.18.1.2 and can be found on-line at policymanual/section8/C224/#p8.2.18_personnel_conduct.

Additionally, USG supports Freedom of Expression as stated in Board Policy 6.5 Freedom of Expression and Academic Freedom found on-line at policymanual/section6/C2653.

The Georgia Institute of Technology (Georgia Tech) is an Equal Employment Opportunity Employer. The Institute is committed to maintaining a fair and respectful environment for all. To that end, and in accordance with federal and state law, Board of Regents policy, and Institute policy, Georgia Tech provides equal opportunity to all faculty, staff, students, and all other members of the Georgia Tech community, including applicants for admission and/or employment, contractors, volunteers, and participants in institutional programs, activities, or services. Georgia Tech complies with all applicable laws and regulations governing equal opportunity in the workplace and in educational activities.

Equal opportunity and decisions based on merit are fundamental values of the University System of Georgia ("USG") and Georgia Tech. Georgia Tech prohibits discrimination, including discriminatory harassment, on the basis of an individual's race, ethnicity, ancestry, color, religion, sex (including pregnancy), national origin, age, disability, genetics, or veteran status in its programs, activities, employment, and admissions. Further, Georgia Tech prohibits citizenship status, immigration status, and national origin discrimination in hiring, firing, and recruitment, except where such restrictions are required in order to comply with law, regulation, executive order, or Attorney General directive, or where they are required by Federal, State, or local government contract.

This is not a supervisory position.
This position does not have any financial responsibilities.
This position will not be required to drive.
This role is not considered a position of trust.
This position does not require a purchasing card (P-Card).
This position will not travel
This position does not require security clearance.

Successful candidate must be able to pass a background check. Please visit employment/pre-employment-screening

Senior Finance Manager

We’re hiring a highly technical Senior Finance Manager to help shape enterprise financial strategy as a real assets platform moves from rapid growth into a more institutional operating model.

This position blends corporate finance, portfolio-level analytics, and structured capital markets work. You’ll be the “modeling engine” for leadership—building institutional-quality models from the ground up and translating outputs into clear recommendations around capitalization, liquidity, and long-term value creation.

You’ll partner closely with senior decision-makers to consolidate portfolio cash flows, evaluate recapitalization paths, test securitization/structured finance options, optimize cost of capital, and uphold rigorous underwriting and diligence standards.

Key Responsibilities

1) Corporate & Portfolio Financial Strategy

• Create and maintain fully integrated three-statement corporate financial models
• Build portfolio roll-ups that consolidate asset-level operating performance and cash flows
• Evaluate recapitalization outcomes (e.g., buyout, minority/structured equity, alternative capital solutions)
• Model securitization concepts backed by stabilized affordable-housing cash flows
• Assess valuation, NAV, and cost-of-capital implications across scenarios
• Deliver sensitivity and scenario analysis to support capital allocation decisions

2) Capital Markets & Capital Stack Optimization

• Analyze refinancing approaches and structured debt alternatives
• Model multi-tranche debt structures and distribution waterfalls
• Support leverage strategy, liquidity planning, and covenant monitoring
• Produce investor-ready materials, return analytics, and capital partner reporting
• Assist with negotiations alongside lenders, equity partners, and other institutional counterparties
• Ensure adherence to JV structures, loan terms, and related compliance requirements

3) Advanced Modeling & Decision Analytics

• Build/upgrade LBO, cash flow waterfall, portfolio coverage, and capital pacing models
• Develop distribution schedules and liquidity/runway projections (13-week and longer-range)
• Standardize modeling templates to improve repeatability and controls
• Provide crisp, decision-ready insights to senior leadership

4) Affordable Housing Underwriting & Transaction Support (LIHTC-focused)

• Oversee underwriting for development and acquisition opportunities
• Improve underwriting tools and submission processes for tax credit transactions
• Lead financial diligence, data room readiness, and documentation hygiene
• Support debt, tax credit equity, and transaction closing activities
• Coordinate with internal teams and external stakeholders through execution

5) FP&A Leadership

• Own consolidated budgeting and forecasting
• Convert property-level data into corporate dashboards and management reporting
• Drive variance analysis, risk identification, and forecasting accuracy improvements
• Implement QA standards and financial controls across models and reporting
• Coach junior talent and raise the technical modeling bar

Ideal Profile

• 6–10 years of experience in real estate private equity, structured finance/credit, infrastructure investing, corporate development, real estate investment banking, or REIT/real assets FP&A
• Expert-level Excel skills with the ability to build models from a blank sheet
• Hands-on experience with: three-statement models, 13-week cash flow, LBO, portfolio roll-ups, waterfalls, and multi-tranche debt structures
• Strong understanding of capital stack mechanics and return metrics (IRR, MOIC, DSCR, ICR)
• Executive-ready communication: can explain complex outputs clearly and concisely
• Real estate background helpful, but high-caliber technical modelers from adjacent verticals are welcome

Technical Strengths

• Institutional-grade financial modeling
• Capital structure strategy and optimization
• Enterprise valuation and NAV frameworks
• Securitization / structured cash flow modeling
• Debt tranching, coverage, and covenant analytics
• Liquidity forecasting and runway analysis
• Advanced Excel (Power Query/Power Pivot preferred)
• Investor reporting and performance analytics

Granite delivers advanced communications and technology solutions to businesses and government agencies throughout the United States and Canada. We provide exceptional customized service with an emphasis on reliability and outstanding customer support and our customers include over 85 of the Fortune 100. Granite has over $1.85 Billion in revenue with more than 2,100 employees and is headquartered in Quincy, MA. Our mission is to be the leading telecommunications company wherever we offer services as well as provide an environment where the value of each individual is recognized and where each person has the opportunity to further their growth and achieve success.

Granite has been recognized by the Boston Business Journal as one of the "Healthiest Companies" in Massachusetts for the past 15 consecutive years.

Our offices have onsite fully equipped state of the art gyms for employees at zero cost.

Granite's philanthropy is unparalleled with over $300 million in donations to organizations such as Dana Farber Cancer Institute, The ALS Foundation and the Alzheimer's Association to name a few.

We have been consistently rated a "Fastest Growing Company" by Inc. Magazine.

Granite was named to Forbes List of America's Best Employers 2022, 2023 and 2024.

Granite was recently named One of Forbes Best Employers for Diversity.

Our company's insurance package includes health, dental, vision, life, disability coverage, 401K retirement with company match, childcare benefits, tuition assistance, and more.

If you are a highly motivated individual who wants to grow your career with a fast paced and progressive company, Granite has countless opportunities for you.

EOE/M/F/Vets/Disabled

Job Description

We are seeking a highly skilled and experienced Lead AI Engineer to join our dynamic team. The ideal candidate will excel at identifying and articulating complex business problems, and will develop innovative, scalable, and robust AI/ML solutions to address these challenges. Responsibilities will include designing, building, and deploying enterprise-grade AI systems, specifically focused on:

• 
  
• Agentic AI solutions to automate operational processes (e.g., interpreting trouble tickets, performing basic troubleshooting, interacting with online portals, data entry).
  
• Retrieval-Augmented Generation (RAG) and ColBERTv2 pipelines for parsing, indexing, and querying enterprise documents to facilitate answers related to process guidelines, product knowledge, and training materials.
  
• Function calling solutions leveraging Large Language Models (LLMs) to automate and perform precise actions in enterprise workflows.
  
• Developing and applying reinforcement learning strategies to optimize and automate decision-making processes within enterprise operations.
  

This role requires hands-on expertise with model fine-tuning, training pipelines, post-training optimization techniques (e.g., model distillation), classification models, and integrating AI systems within complex enterprise environments.

Duties and Responsibilities

• 
  
• Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models, LLaMA, Mistral).
  
• Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using advanced vector databases (e.g., FAISS, Pinecone, Milvus).
  
• Build and enhance agentic AI systems utilizing frameworks like LangChain, AutoGPT, or similar automation frameworks.
  
• Deploy scalable ColBERTv2 architectures for semantic retrieval and classification.
  
• Create robust pre-processing and post-processing pipelines to enhance model performance, accuracy, and interpretability.
  
• Collaborate closely with cross-functional teams, including product managers, business stakeholders, data scientists, and software engineers.
  
• Implement best practices in model distillation, quantization, and optimization for deployment in production environments.
  
• Ensure compliance with enterprise-grade security, privacy standards, and data governance practices.
  
• Provide leadership and mentorship to team members, supporting their technical development and career growth through coaching, training, and performance feedback.
  
• Drive timely and successful completion of AI/ML projects by setting clear milestones, tracking progress, removing blockers, and aligning resources
  

Required Qualifications

• 
  
• Bachelor's degree in Computer Science, Data Science, Machine Learning, AI, or related fields; advanced degree strongly preferred.
  
• 5+ years of proven experience developing and deploying production-grade AI/ML systems.
  
• Strong programming skills in Python, familiarity with libraries/frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain.
  
• Demonstrated expertise with LLM fine-tuning (e.g., LoRA, PEFT), distillation, and model optimization.
  
• Practical experience implementing RAG pipelines with embedding technologies and vector stores (e.g., FAISS, Pinecone).
  
• Proven track record building agentic AI systems capable of interacting with multiple enterprise applications and platforms.
  
• Solid understanding of NLP techniques, Transformer architectures, semantic search, and document retrieval technologies (e.g., ColBERT).
  
• Hands-on experience with reinforcement learning techniques, including designing, training, and deploying reinforcement learning models.
  

Preferred Qualifications:

• 
  
• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related field.
  
• Familiarity with cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI).
  
• Experience with containerization (Docker, Kubernetes) and deployment pipelines (CI/CD).
  
• Knowledge of advanced AI frameworks and model inference engines such as Triton Inference Server, TensorRT, and ONNX.
  
• Familiarity with model monitoring, observability tools, and techniques to ensure long-term reliability and performance.
  
• Strong communication and interpersonal skills with the ability to clearly articulate complex technical solutions to non-technical stakeholders.
  
• Experience in regulated industries or environments requiring strict compliance and data governance standards.
  

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

The Content Understanding team builds machine learning models that "read" Pinterest content-images, text, and video-to produce high-quality semantic signals (e.g., embeddings, localization, quality/safety labels). These signals power relevance and retrieval for Homefeed, Search, Related Pins, and Ads, and also support integrity use cases like spam and low-quality detection. We work end-to-end: from data and labeling strategy, to model training and evaluation, to low-latency serving and monitoring at Pinterest scale. The role is ideal for a senior modeler who also enjoys developing, productionizing models and leading technical direction across teams.

What you'll do:

• 
  
• Lead modeling strategy for content understanding (vision, NLP, multimodal), including architecture selection, training approach, and evaluation methodology.
  
• Design and ship production models that generate content signals such as embeddings and classifications used across multiple product surfaces.
  
• Own the full ML lifecycle: data/labeling strategy (human labels + weak supervision), training pipelines, offline evaluation, online experimentation, deployment, and monitoring/retraining.
  
• Partner with infra/platform teams to ensure scalable, reliable training/serving (latency, cost, observability, rollout safety).
  
• Collaborate with signal-consuming teams (ranking, retrieval, integrity, ads) to define signal contracts, adoption patterns, and success metrics.
  
• Provide technical leadership through design reviews, mentoring, and raising the quality bar for modeling and ML engineering practices.
  

What we're looking for:

• 
  
• M.S/ PhD degree in Computer Science, Statistics or related field.
  
• Significant industry experience building software and ML pipelines/systems, including technical leadership (project/tech lead or equivalent).
  
• Strong proficiency in Python and at least one ML stack such as PyTorch / TensorFlow, plus solid software engineering fundamentals.
  
• Proven experience training and deploying ML models to production, including model versioning, rollouts, monitoring, and retraining strategies.
  
• Deep hands-on experience in content understanding domains, such as:
  
  • 
    
  • computer vision (classification, detection, representation learning),
    
  • NLP (text classification, entity/topic modeling),
    
  • multimodal / embedding models (e.g., transformer-based representations).
    
  
  
• Experience working with large-scale datasets and distributed compute (e.g., Spark-like ecosystems, distributed training, GPU environments).
  
• Strong applied skills in evaluation and experimentation: defining metrics, offline/online alignment, A/B testing, debugging regressions, and model quality analysis.
  
• Demonstrated ability to influence across teams and drive ambiguous problem areas to measurable outcomes.
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

In-Office Requirement Statement:

• 
  
• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  
• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
  

#LI-REMOTE

#LI-SM4

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

*At Securian Financial the internal position title is Data Science Sr Con.*

Position Overview

As a Lead Data Scientist at Securian Financial, you are a recognized expert and technical leader within the organization. You will apply deep analytical and machine learning expertise to solve complex enterprise problems while shaping the technical direction of data science and AI initiatives. You seek to understand first, build scalable solutions that drive strategic growth and value, and thrive in a collaborative, teamwork-oriented environment.

You will play a key role in advancing our enterprise AI and advanced analytics capabilities, influencing tooling standards, MLOps practices, and responsible AI adoption across the organization. Our company values innovation, collaboration, and excellence, and we offer a supportive and inclusive environment where diverse perspectives are encouraged and professional growth is prioritized.

Key Responsibilities

• Design, develop, and productionize advanced machine learning and AI models in partnership with data engineering and software engineering teams.

• Establish and promote MLOps best practices, including experiment tracking, model versioning, reproducibility, CI/CD, and model monitoring using tools such as MLflow and DSpy.

• Lead the design and evaluation of AI and generative AI solutions, including LLM-based systems, and agent-based workflows.

• Collaborate with cross-functional team to identify, prioritize, and deliver high-impact, data-driven solutions.

• Communicate complex analytical and model-driven insights to technical and non-technical audiences through clear narratives, reports, and presentations.

• Ensure model quality, robustness, and regulatory alignment through rigorous testing, validation, and explainability techniques.

• Drive adoption of enterprise standards for data science, machine learning, and responsible AI.

• Identify opportunities for process improvements and automation using advanced analytics and AI techniques.

• Lead and mentor more junior data scientists, providing guidance and support in their professional development while working on projects.

Preferred Qualifications

• A Master's or PhD degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• At least 5 years of experience in data science or a related field, with a minimum of 2 years in a project leadership role.

• Experience building and deploying production solutions

• Experience with MLOps tools and practices, including MLflow (or similar) for experiment tracking and model management.

• 2+ years of experience in Insurance, actuarial, or a related field

• Proficiency in programming languages such as Python

• Strong expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).

• Solid understanding of statistical analysis, data visualization, data wrangling techniques, NLP approaches, ML model selection.

• Solid understanding of model approaches to satisfy regulatory requirements regarding explainability/interpretability of advanced AI/ML models

• Excellent problem-solving skills and the ability to think critically and analytically.

• Strong communication and presentation skills, with the ability to convey complex concepts to non-technical audiences.

• Demonstrated ability to manage multiple projects and prioritize tasks effectively.

• A passion for continuous learning and staying current with industry trends and developments.

Preferred Skills

• Experience with natural language processing (NLP), LLMs, prompt engineering, and advanced ML models.

• Familiarity with modern ML debugging, evaluation, and optimization tools such as DSpy or equivalent.

• Knowledge of responsible AI practices, including bias detection, fairness assessment, and model risk management.

• Knowledge of data governance and data privacy regulations.

• Background in finance, healthcare, or other specialized industries.

#LI-hybrid **This position will be in a hybrid working arrangement.**

Securian Financial believes in hybrid work as an integral part of our culture. Associates get the benefit of working both virtually and in our offices. If you're in a commutable distance (90 minutes), you'll join us 3 days each week in our offices to collaborate and build relationships. Our policy allows flexibility for the reality of business and personal schedules.

The estimated base pay range for this job is:

Pay may vary depending on job-related factors and individual experience, skills, knowledge, etc. More information on base pay and incentive pay (if applicable) can be discussed with a member of the Securian Financial Talent Acquisition team.

Be you. With us. At Securian Financial, we understand that attracting top talent means offering more than just a job - it means providing a rewarding and fulfilling career. As a valued member of our high-performing team, we want you to connect with your work, your relationships and your community. Enjoy our comprehensive range of benefits designed to enhance your professional growth, well-being and work-life balance, including the advantages listed here:

Paid time off:

• We want you to take time off for what matters most to you. Our PTO program provides flexibility for associates to take meaningful time away from work to relax, recharge and spend time doing what's important to them. And Securian Financial rewards associates for their service by providing additional PTO the longer you stay at Securian.

• Leave programs: Securian's flexible leave programs allow time off from work for parental leave, caregiver leave for family members, bereavement and military leave.

• Holidays: Securian provides nine company paid holidays.

Company-funded pension plan and a 401(k) retirement plan: Share in the success of our company. Securian's 401(k) company contribution is tied to our performance up to 10 percent of eligible earnings, with a target of 5 percent. The amount is based on company results compared to goals related to earnings, sales and service.

Health insurance: From the first day of employment, associates and their eligible family members - including spouses, domestic partners and children - are eligible for medical, dental and vision coverage.

Volunteer time: We know the importance of community. Through company-sponsored events, volunteer paid time off, a dollar-for-dollar matching gift program and more, we encourage you to support organizations important to you.

Associate Resource Groups: Build connections, be yourself and develop meaningful relationships at work through associate-led ARGs. Dedicated groups focus on a variety of interests and affinities, including:

• Mental Wellness and Disability

• Pride at Securian Financial

• Securian Young Professionals Network

• Securian Multicultural Network

• Securian Women and Allies Network

• Servicemember Associate Resource Group

For more information regarding Securian's benefits, please review our Benefits page.

This information is not intended to explain all the provisions of coverage available under these plans. In all cases, the plan document dictates coverage and provisions.

Securian Financial Group, Inc. does not discriminate based on race, color, religion, national origin, sex, gender, gender identity, sexual orientation, age, marital or familial status, pregnancy, disability, genetic information, political affiliation, veteran status, status in regard to public assistance or any other protected status. If you are a job seeker with a disability and require an accommodation to apply for one of our jobs, please contact us by email at , by telephone (voice), or 711 (Relay/TTY).

To view our privacy statement click here

To view our legal statement click here

• 
  
• Provide deep technical leadership to a portfolio of high impact data science initiatives involving sales and advisor experience. Identify the optimal sets of data, models, training, and testing techniques required for successful product delivery. Remove complex technical impediments
  
• Leverage your experience and skills to identify new opportunities where data science and AI can improve experiences, gain efficiencies, and generate sales.
  
• Manage team members in AI/ML and model development, testing, training, and tuning. Apply hands-on experience to ensuring best-in-class model development. Mentor team members in technical skill development and product ownership.
  
• Communicate clearly and concisely, in writing and verbally, all facets of model design and development. Continuously look for insights in models developed and generate new ideas for model improvement.
  
• Manage external vendors in the execution of parts of the data science development process as needed.
  
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code on Prudential's AI/ML platform.
  
• Bring a deep understanding of relevant and emerging technologies, give technical direction to team members and embed learning and innovation in the day-to-day.
  
• Work on significant and unique issues where analysis of situations or data requires an evaluation of intangible variables and may impact future concepts, products or technologies.
  
• Familiarity with Python, SQL, AWS, and JIRA.
  
• Familiarity with LLMs, deployment of LLMs, RAG, LangChain, LangGraph, and Agentic AI concepts.
  

• 
  
• Applied Statistics, Computer Science, or Engineering or experience in related fields with a focus on machine learning, AI, and LLMs.
  
• Junior category industry experience with responsibility for developing and delivering advanced quantitative, AI/ML, analytical and statistical solutions.
  
• Ability to lead a small team with minimal guidance and effectively leverage diverse ideas, experiences, thoughts and perspectives to the benefit of the organization to deliver AI products.
  
• Ability to influence business stakeholders and to drive adoption of AI/ML solutions.
  
• Experience with agile development methodologies, Test-Driven Development (TDD), and product management.
  
• Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business
  
• Demonstrated ability to mentor and operational management of data science team based on project requirements, resourcing requirements, and planning dependencies as appropriate, anticipate risks and bottlenecks and proactively takes actions
  
• Excellent problem solving, communication and collaboration skills, and stakeholder management
  
• Significant experience and/or deep expertise with several of the following:
  
• Machine Learning and AI: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, interpreting and monitoring machine learning models. Expertise in traditional machine learning models (unsupervised, XGBoost, etc.) and Large Language Models (OpenAI, Claude).
  
• Model Deployment: Understanding of model development life cycle, CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness, etc.), A/B testing, and pipeline frameworks such as AWS SageMaker, and newer AWS/Azure Agentic AI infrastructure products.
  
• Data Acquisition and Transformation: Acquiring data from disparate data sources using APIs and SQL. Transform data using SQL and Python. Visualizing data using a diverse tool set including but not limited to Python.
  
• Database Management Systems: Knowledge of how databases are structured and function in order use them efficiently. May include multiple data environments, cloud/AWS, primary and foreign key relationships, table design, database schemas, etc.
  
• Data Analysis and Insights: Analyzing structured and unstructured data using data visualization, manipulation, and statistical methods to identify patterns, anomalies, relationships, and trends.
  
• Programming Languages: Python and SQL