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Sr. Data Engineer (PySpark & Python + AI Tools Exp.) - (Only W2 or 1099)

Charlotte, NC (Hybrid)

12+ Months Contract

Job Description:

We are currently seeking a Senior Data Engineer with hands-on coding experience and a strong background in Python, PySpark, and Object-oriented programming.

The ideal candidate will be responsible for designing, developing, and implementing new features to our existing framework using PySpark and Python.

This position requires a deep understanding of data transformation and the ability to create standalone scripts based on given business logic. Also, exposure to AI Tools and building any AI applications will be advantage.

Key Responsibilities:

• Design, develop, and optimize large-scale data pipelines using PySpark and Python.
• Implement and adhere to best practices in object-oriented programming to build reusable, maintainable code.
• Write advanced SQL queries for data extraction, transformation, and loading (ETL).
• Collaborate closely with data scientists, analysts, and stakeholders to gather requirements and translate them into technical solutions.
• Troubleshoot data-related issues and resolve them in a timely and accurate manner.
• Leverage AWS cloud services (e.g., S3, EMR, Lambda, Glue) to build and manage cloud-native data workflows (preferred).
• Participate in code reviews, data quality checks, and performance tuning of data jobs.

Required Skills & Qualifications:

• 6+ years of relevant experience in a data engineering or backend development role.
• Strong hands-on experience with PySpark and Python, especially in designing and implementing scalable data transformations.
• Solid understanding of Object-Oriented Programming (OOP) principles and design patterns.
• Proficient in SQL, with the ability to write complex queries and optimize performance.
• Strong problem-solving skills and the ability to troubleshoot complex data issues independently.
• Excellent communication and collaboration skills.
• Hands-on experience with AI Tools.

Preferred Qualifications (Nice to Have):

• Experience working with AWS cloud ecosystem (S3, Glue, EMR, Redshift, Lambda, etc.).
• Exposure to data warehousing concepts, distributed computing, and performance tuning.
• Familiarity with version control systems (e.g., Git), CI/CD pipelines, and Agile methodologies.
• Exposure to AI Tools and hands-on experience of building any AI applications.

Job Title: Senior Automation Engineer

Location: Hillsboro, Oregon

Job Type: Full-Time

Job Description:

We are seeking a highly experienced Senior Automation Engineer to join our advanced software and embedded systems team. The ideal candidate will have deep expertise in Python automation (Pytest), Robot Framework, and QNX environments, with strong skills in UX/UI automation and testing. This role involves enhancing and migrating automation frameworks, debugging complex integrations, and working closely with cross-functional teams to deliver high-quality test automation solutions for embedded systems and entertainment platforms.

Key Responsibilities

Automation Framework Development

• Architect, develop, and maintain automation frameworks primarily using Python and Pytest.
• Lead migration of existing Robot Framework tests to Python/Pytest equivalents.
• Build reusable fixtures, utilities, wrapper layers, and automation components to support large test suites.

Test Execution & Optimization

• Analyze and interpret Robot Framework keyword libraries; enable efficient reuse within Python-based executions.
• Optimize hybrid execution flows involving both Pytest and Robot Framework assets.
• Execute and maintain UI and device automation tests using tools such as Appium, Selenium, or equivalent frameworks.

Cross-Layer Debugging & Integration

• Independently debug cross-layer automation issues involving Python, Robot Framework, device tools, and operating systems.
• Integrate automation frameworks with CI/CD pipelines and tools (e.g., Jenkins, GitLab, Azure DevOps).

Collaboration & Mentorship

• Mentor and guide junior automation engineers, establishing good coding practices, test design patterns, and quality standards.
• Work collaboratively with software engineers, product developers, and QA teams to enhance automation coverage and reliability.

System & Environment Interaction

• Work with QNX OS, virtualization systems (Hypervisor), and cloud environments (AWS).
• Engage with hardware interfacing (USB, Ethernet, multimedia interfaces) and hardware simulation/ fault-injection where applicable (nice-to-have).

Required Skills & Experience

• 7–10 years experience in automation engineering with 5+ years hands-on Python automation using Pytest.
• Practical experience with Robot Framework including keywords, variables, resources, and large keyword repositories.
• Strong skills in UI automation using tools such as Appium/Selenium.
• Solid understanding of modular test design and maintainable patterns (page-object, keyword patterns).
• Experience with QNX (Posix) operating system, virtualization (e.g., Hypervisor), and cloud-based environments (preferably AWS).
• Good understanding of Git, branching strategies, and CI/CD workflows.
• Proven ability to debug complex, multi-layered test automation environments.

Preferred Qualifications

• Exposure to embedded systems, aviation, or high-volume regression environments.
• Experience in framework migration, cross-framework interoperability, or keyword reuse models.
• Background in hardware interactions and media/UX systems (multimedia I/O, touch interactions).
• Familiarity with fault injection tools and hardware simulation techniques.
• Bachelor’s degree in Computer Science, Electronics, or related technical field.

Nice-to-Have Skills

• Hardware interfacing (USB, Ethernet), multimedia interfaces (touch, audio/video).
• Fault-injection and hardware simulation experience.
• Knowledge of peripheral communication protocols (e.g., GMSL, IP).

Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA

Title: Machine Learning Engineer

Location: San Jose, CA

Responsibilities:

• Productize and optimize models from Research into reliable, performant, and cost-efficient services with clear SLOs (latency, availability, cost).
• Scale training across nodes/GPUs (DDP/FSDP/ZeRO, pipeline/tensor parallelism) and own throughput/time-to-train using profiling and optimization.
• Implement model-efficiency techniques (quantization, distillation, pruning, KV-cache, Flash Attention) for training and inference without materially degrading quality.
• Build and maintain model-serving systems (vLLM/Triton/TGI/ONNX/TensorRT/AITemplate) with batching, streaming, caching, and memory management.
• Integrate with vector/feature stores and data pipelines (FAISS/Milvus/Pinecone/pgvector; Parquet/Delta) as needed for production.
• Define and track performance and cost KPIs; run continuous improvement loops and capacity planning.
• Partner with ML Ops on CI/CD, telemetry/observability, model registries; partner with Scientists on reproducible handoffs and evaluations.

Educational Qualifications:

• Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master’s preferred (or equivalent industry experience).
• Strong systems/ML engineering with exposure to distributed training and inference optimization.

Industry Experience:

• 3–5 years in ML/AI engineering roles owning training and/or serving in production at scale.
• Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements.
• Experience collaborating across Research, Platform/Infra, Data, and Product functions.

Technical Skills:

• Familiarity with deep learning frameworks: PyTorch (primary), TensorFlow.
• Exposure to large model training techniques (DDP, FSDP, ZeRO, pipeline/tensor parallelism); distributed training experience a plus
• Optimization: experience profiling and optimizing code execution and model inference: (PTQ/QAT/AWQ/GPTQ), pruning, distillation, KV-cache optimization, Flash Attention
• Scalable serving: autoscaling, load balancing, streaming, batching, caching; collaboration with platform engineers.
• Data & storage: SQL/NoSQL, vector stores (FAISS/Milvus/Pinecone/pgvector), Parquet/Delta, object stores.
• Write performant, maintainable code
• Understanding of the full ML lifecycle: data collection, model training, deployment, inference, optimization, and evaluation.

Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA

Job Title: Senior Software Engineer

Reports To: Manager of Application Development

About the Role:

The Senior Software Engineer is a hands-on technical leadership position responsible for designing, building, and maintaining high-quality software solutions. This role emphasizes both individual development work and ownership of design decisions for features and subsystems. Modern tools, including AI-assisted development and architectural support, are leveraged to drive delivery while maintaining accountability for technical outcomes.

Responsibilities:

• Design, implement, test, and maintain scalable, secure, and reliable applications and services.
• Act as a senior technical contributor, with responsibility for the design and implementation of features and subsystems.
• Contribute actively to development tasks, applying advanced coding expertise in several programming languages and frameworks.
• Participate in architectural discussions and support incremental evolution of systems with team leads.
• Conduct code reviews and mentor engineering team members, fostering best practices and ongoing improvement.
• Translate requirements from product owners, business analysts, and stakeholders into technical solutions.
• Identify and mitigate technical risks in assigned systems and projects.
• Support and enhance cloud-based applications (Azure, AWS) with emphasis on performance, reliability, and scalability.
• Collaborate effectively with onshore and offshore teams to ensure successful project execution.
• Keep abreast of industry trends and new technologies to encourage innovation.
• Utilize AI-assisted tools to expedite design, documentation, and implementation, while ensuring technical quality.
• Lead and support AI-related initiatives, drawing on prior experience with AI/ML technologies; recommend and implement suitable AI tools and frameworks.
• Test and demonstrate emerging AI tools and platforms via proofs of concept (POCs) to highlight business value.
• Guide customers in leveraging AI to optimize business processes; support teams working on business-facing AI efforts.
• Collaborate with stakeholders to contribute to defining an AI roadmap aligned with organizational strategy and technology objectives.

Qualifications:

• Bachelor’s degree in Computer Science, Software Engineering, or a related field; Master’s degree preferred.
• A minimum of 5 years in a Senior Software Engineer, Lead Developer, or similar role, with proven success delivering production systems.

Required Skills:

• Strong understanding of software development methodologies (e.g., Agile, DevOps) and architectural frameworks.
• Proficient in programming languages such as C#, Python; excellent problem-solving and critical thinking skills.
• Web Development: Experience with modern front-end frameworks (e.g., React, Vue.js).
• Mobile Development: Knowledge of mobile app development tools (e.g., Cordova, Ionic).
• Cloud Development: Experience managing cloud-hosted applications, including Azure Functions and Event Hubs.
• Database Management: Ability to develop and debug stored procedures, views, and tables in SQL Server and MySQL; basic database administration for data integrity and security.
• API Development: Skilled at designing, building, and debugging APIs; experience with RESTful APIs and tools like POSTMAN and SOAPUI.
• DevOps: Designing branching strategies; implementing and maintaining CI/CD pipelines for test automation and deployment.
• Containerization: Experience with Docker and Kubernetes for application development and deployment.
• Security: Understanding of secure coding and application security best practices.

Preferred Skills:

• Ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Effective teamwork, working with cross-functional groups including developers, project managers, and analysts.
• Strong problem-solving abilities and the capacity to make effective decisions under constraints.
• Leadership through mentoring and influencing technical direction.
• Adaptability to new technologies and changing environments.
• Critical thinking in evaluating options and making informed decisions.
• Effective time management across multiple projects.
• Empathy for team and stakeholder perspectives to foster collaboration.

Job Title: Embedded Validation Engineer

Location: Charlotte, NC

Job Type: Full-Time

Role Overview

We are seeking a technically strong Embedded Validation Engineer to serve as the Controls and Quality Assurance (QA) point of contact for lab validation and sustaining programs. The role focuses on requirements-based validation, disciplined test execution, defect reporting, and traceability across multiple product programs.

The ideal candidate will work closely with Systems Engineering, Product Development, and QA teams to validate embedded control systems, execute lab testing, and improve test automation and validation processes.

Key Responsibilities

Requirements-Based Validation

• Collaborate with Systems Engineering teams to derive validation strategies and test plans from system requirements.
• Develop and maintain requirement-to-test case traceability.
• Ensure validation activities align with product specifications and engineering requirements.

Lab Test Execution

• Serve as the Controls Validation Point of Contact (POC) for lab validation activities.
• Execute validation tests on prototype hardware and embedded control systems.
• Document test procedures and record pass/fail outcomes with technical accuracy.

Documentation & Traceability

• Maintain organized test documentation including test plans, execution logs, and validation reports.
• Ensure traceability between requirements, test cases, and defect reports.

Defect Reporting & Tracking

• Identify, document, and report defects with clear technical descriptions and reproducible steps.
• Collaborate with development teams to analyze root causes and track defect resolution.

Reporting & Quality Reviews

• Prepare concise 2–3 slide technical summaries of test results and validation findings.
• Present validation updates during PRQRB/SQA or departmental review meetings.

Test Bench & HIL Development

• Design and build test bench setups and Hardware-in-the-Loop (HIL) simulators for validation.
• Support legacy platforms and existing validation environments.

Automation Development

• Contribute to Python-based test automation and validation frameworks.
• Identify opportunities to improve test efficiency through automation.

Product Support & Continuous Improvement

• Support new product development, sustaining engineering, and validation process improvements.
• Drive enhancements in test infrastructure, lab workflows, and validation methodologies.

Required Qualifications

• Bachelor’s degree in Controls Engineering, Software Engineering, Electrical Engineering, or related field.
• 5+ years of experience in embedded systems validation, SQA, or controls testing.
• Strong understanding of Software Quality Assurance (SQA) fundamentals, including test execution and documentation.
• Experience validating embedded control systems and equipment controls.
• Hands-on experience with lab-based validation and prototype testing.
• Knowledge of controls inputs/outputs, sensors, and system interfaces.
• Experience with bench wiring, test setup, and instrumentation.
• Strong analytical skills and familiarity with engineering basics such as heat exchangers and unit conversions.
• Experience with Python scripting and test automation.

Title: Python with AI(Only w2)

Location: Atlanta GA(Onsite/Only Locals)

Must have mins 10-12 years of overall years of experience

Must haves.

• Strong Python programming (OOP, typing, async programming).
• Experience with API development (FastAPI or Flask).
• PY-test framework knowledge for unit testing.
• Git hub branching familiarity
• Framework development experience with PyTorch, TensorFlow, Hugging Face Transformers, LangChain, OpenAI API
• Basic Cloud knowledge like server less compute, http traffic, CICD concepts

Nice to Have:

• Deep Learning: Neural networks, CNNs, RNNs, transformers, attention mechanisms.
• Azure: resource groups, container apps, vnet, logging, cosmos db.
• SQL (Query writing) experience like SQL server/Azure SQL/Oracle/PostgreSQL
• API security with AuthN/AuthZ understanding of OpenID or oAuth2 flows

If I missed your call ! Please drop me a mail.

Thank you,

Harish

Talent Acquisition

Astir IT Solutions, Inc - An E-Verified Company

Email:

Direct : 7326946000*788

50 Cragwood Rd. Suite # 219, South Plainfield, NJ 07080

Senior Pega Developer ( Pega / Python / CDH )

Optomi, in partnership with, an enterprise Telecom client, is seeking a Senior Pega Developer to sit in their Stamford, CT office! There is a hybrid structure of 4 days on site in the office, with flexibility for working from home once weekly. This position requires hands-on experience developing with Pega systems, ideally Customer Decision Hub (CDH) with Python for scripting.

What the Right Candidate Will Enjoy:

• 2025 Awards include "Forbes Accessibility 100", "Fortune America's Most Innovative Companies", "Forbes America's Best Employers for Tech Workers", etc.
• Directly develop applications impacting over 25M+ customers across 41 states!
• A hybrid office structure that allows for working from home!

Experience of the Right Candidate:

• Proven track record with 5-6 years of experience working with Customer Decision Hub (CDH), demonstrating deep understanding and ability to leverage CDH for personalized customer interactions and decisioning.
• Certifications: Relevant Pega certifications are required (e.g., Certified Pega Business Architect, Certified Pega System Architect).
• Python: Strong proficiency in Python for scripting and automation tasks, with experience in integrating Python solutions within Pega applications.
• SQL: Solid experience with SQL for database management and querying, including the ability to write complex queries and optimize database performance.
• Apache Airflow (Optional): Experience with Apache Airflow for orchestrating complex workflows is a plus but not mandatory.

Responsibilities of the Right Candidate:

• Develop and implement solutions using Pega CDH to enhance customer engagement strategies.
• Collaborate with cross-functional teams to design and optimize workflows and decisioning processes.
• Utilize Python and SQL to support data-driven decision-making and application enhancements.
• Optionally, leverage Apache Airflow for efficient workflow automation and scheduling.
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills for effective collaboration with team members and stakeholders.
• Ability to thrive in a fast-paced, dynamic environment and adapt to evolving project requirements.

About Us 

Smart Reimbursement Inc. (SRI) is a healthcare finance and analytics firm that provides innovative solutions to reimbursement challenges faced by hospitals. We combine deep policy expertise with advanced data tools to help hospitals. 

Our mission is to improve the healthcare industry by leveraging technology to automate and streamline financial reporting processes, enabling hospitals to focus on providing the highest quality of care to patients. Although SRI has been in business since 2011, our culture is more like an early-stage startup, and we prioritize experimentation, innovation, and collaboration. 

The Role 

We are hiring a Python Data Analyst to deepen ownership of our internal analytics models and improve the reliability and scalability of our delivery engine. This role will focus on preparing data, running internal Python models, troubleshooting issues, and improving performance and automation across workflows. 

You will work closely with our delivery leadership and technical subject matter experts to learn existing workflows quickly, then contribute improvements over time. 

Responsibilities 

• Prepare and shape large healthcare datasets (claims, remits, transactions, reimbursement-related files) for internal Python models. 
• Operate and support internal Python models reliably, including troubleshooting and root-cause debugging. 
• Work with very large datasets (100M+ rows) and implement pragmatic approaches when standard tools are insufficient. 
• Build and maintain efficient data pipelines for recurring and ad-hoc analytics projects. 
• Automate data transformation and reporting workflows with clean, reusable code. 
• Support the preparation of audit-ready workpapers and other client-ready documentation. 
• Participate in internal and client meetings as needed to clarify goals and communicate findings. 
• Improve documentation, internal tools, and project templates. 

What Success Looks Like 

• You can run internal model workflows end-to-end with minimal oversight. 
• You can diagnose and resolve issues independently and improve reliability for the broader team. 
• You deliver meaningful improvements to performance, automation, and repeatability. 
• You are a strong team player who supports delivery execution and reduces friction. 

Required Qualifications 

• Advanced Python skills (ability to run, own, and improve an analytics codebase, not just write one-off scripts). 
• Strong experience working with large datasets and performance constraints. 
• Advanced MS Excel skills (complex formulas, pivot tables, data validation, and ability to work with larger datasets). 
• Comfort in Jupyter notebooks and reproducible workflows (pandas required). 
• Proven debugging ability and strong analytical judgment. 
• Experience working with sensitive or regulated data; HIPAA/PHI experience strongly preferred. 
• Clear communication and a collaborative working style. 

Nice to Have 

• Experience with healthcare data or hospital finance/reimbursement workflows 
• Familiarity with EPIC healthcare data 
• Experience optimizing data workflows (e.g., parquet/arrow, duckdb, polars, dask, spark, databases) 
• SQL proficiency 

Location, Logistics, and Process 

• Nashville Hybrid or Fully Remote. 
• Background check required. 
• This role involves HIPAA-protected data and requires strict data security practices. 
• Interview process includes a Python technical assessment. 

Compensation & Benefits 

This role offers a base salary of $130,000–$150,000, depending on experience, plus a performance-based bonus. Benefits include health, dental, and vision insurance, and a 401(k) with employer match. 

Onsite AI Engineer - Construction Industry Focus

New Haven, CT - Onsite 5 days per week

• Initial Assignment: Fully onsite 5 days per week at a construction site in Ft. Myers (FL) or New Haven (CT) for 1 year
• Post-Assignment: Relocation to one of the corporate offices for hybrid employment: Boston, MA (preferred), New York City (NY), New Haven (CT), Herndon (VA), West Palm Beach (FL), or Estero (FL)

Role Summary

As the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Responsibilities

• Workflow discovery and redesign: Lead Lean/Six Sigma workshops; map value streams; log high-impact AI agent opportunities that improve field efficiency.
• AI agent development: Build and deploy multiple production-ready AI agents using Copilot Studio, Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks. Integrate agents into Teams/SharePoint on the front end and Databricks Lakehouse or other enterprise data sources on the back end.
• RAG pipelines and LLMOps: Design and operate retrieval-augmented generation (RAG) pipelines with Databricks Delta Tables, Unity Catalog, and Vector Search (or Spark/Hadoop equivalents). Monitor cost, latency, adoption, and model drift.
• Cross-cloud orchestration: Blend OpenAI, Azure OpenAI, and AWS Bedrock services through secure custom connectors to maximize flexibility and adoption.
• Data integration: Partner with Data Engineering to deliver ETL/ELT pipelines, API integrations, and event-driven connectors that feed RAG pipelines and AI agents.
• Change management and adoption: Train field teams, gather feedback, iterate quickly, and embed agents into SOPs. Track usage and ROI with adoption metrics and behavior-change KPIs.
• Stakeholder communication: Translate technical results into business value for leadership and clients. Contribute use cases and playbooks for the “Construction Site of the Future.”
• Compliance and hand-offs: Ensure all AI solutions meet the company’s data governance and security standards. Draft clear user stories and specs for escalation to central AI/Data Engineering teams when necessary.

Qualifications

• 4+ years in AI engineering, data science, or ML-focused software engineering.
• Proven experience building multiple AI agents in production environments.
• 2+ years of hands-on experience with LLMs, RAG pipelines, and LLMOps practices.
• Must have strong traditional software engineering background in Python

Bonus Points

• Experience in construction, manufacturing, or other process-heavy industries.
• Advanced degree in a technical field.