TSSCI w/ Poly Machine Learning Engineer

Insight Global
Surry, VA, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Amazon Web Services Microsoft Azure Computer Programming Continuous Integration Data Structures Software Design Patterns DevOps Programming Tools Python (Programming Language) Machine Learning NoSQL
+14 more
Open Source Technology Ansible Software Engineering SQL Databases Google Cloud Large Language Models Git Containerization Kubernetes Infrastructure Automation Frameworks Information Technology Rancher Machine Learning Operations Docker

Job description

Develop and maintain machine learning pipelines and applications using Python and modern ML

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

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