TSSCI w/ Poly Machine Learning Engineer

Insight Global; Chantilly (VA); On-site; USD 100,000 - 130,000; Full time

Job summary

Insight Global is seeking a Machine Learning Engineer based in Chantilly, Virginia, with strong proficiency in Python and experience in machine learning engineering. This role involves developing and maintaining ML pipelines, optimizing algorithms for LLM integration, and collaborating with cross-functional teams to deliver high-quality technical solutions.

The ideal candidate will have a Bachelor's degree and at least 5 years of professional experience, with skills in Git, Docker, and cloud platforms. An active TS/SCI clearance is mandatory.

Qualifications

• Active TS/SCI clearance with Poly.
• 5 years of professional experience in software development or machine learning engineering.
• Understanding of AI/ML best practices.

Responsibilities

• Develop and maintain machine learning pipelines and applications using Python.
• Build RESTful APIs and microservices to serve ML models in production.
• Conduct testing and debugging of ML applications.

Skills

Python programming

Machine learning engineering

Git version control

Docker containerization

Large Language Models

SQL and/or NoSQL

Problem-solving

Communication skills

Education

Bachelor's degree in computer science, software engineering, data science, or related technical field

Master's degree in computer science or related field

Tools

Docker

Kubernetes

CI/CD tools

Job description

Job Description

Responsibilities

• Develop and maintain machine learning pipelines and applications using Python and modern ML frameworks.
• Implement and optimize algorithms for large language model (LLM) integration and deployment.
• Build RESTful APIs and microservices to serve ML models in production environments.
• Write clean, maintainable, and well‑documented code following object‑oriented programming principles.
• Collaborate with cross‑functional teams to understand requirements and translate them into technical solutions.
• Work with databases (SQL, NoSQL, and Vector) to manage training data, model artifacts, and application state.
• Containerize ML applications using Docker for consistent deployment across environments.
• Utilize Git for version control and participate in code reviews to maintain code quality.
• Conduct testing and debugging of ML applications to ensure reliability and accuracy.
• Support the deployment and monitoring of AI/ML models in cloud environments.
• Stay current with emerging trends in machine learning, LLMs, and AI engineering best practices.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [e-mail]. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• Active TS/SCI clearance with Poly.
• Bachelor's degree in computer science, software engineering, data science, or related technical field with 5 years of professional experience in software development or machine learning engineering.
• Strong proficiency in Python programming with solid understanding of object‑oriented programming (OOP) concepts, design patterns, data structures, and algorithms.
• Experience with development tools and practices including Git version control, Docker containerization, and database management (SQL and/or NoSQL).
• Knowledge of LLM technologies including exposure to Large Language Models, orchestration frameworks (LangChain, LangGraph).
• Understanding of RAG architectures and vector databases (ChromaDB, Pinecone, Weaviate, or similar) for building intelligent retrieval systems.
• Strong problem-solving abilities, attention to detail, excellent communication skills, and eagerness to learn in a collaborative team environment.
• Master's degree in computer science or related field.
• Experience with cloud platforms (AWS, Azure, or Google Cloud) and knowledge of MLOps practices for ML model deployment and monitoring.
• Experience with container orchestration and DevOps including Kubernetes, Rancher, CI/CD pipelines, and infrastructure automation tools like Ansible.
• Contributions to open‑source ML projects and familiarity with Agile development methodologies.