TSSCI w/ Poly Machine Learning Engineer

Insight Global
Surry, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Surry, United States of America

Tech stack

Agile Methodologies
Amazon Web Services (AWS)
Azure
Computer Programming
Continuous Integration
Data Structures
Software Design Patterns
DevOps
Programming Tools
Python
Machine Learning
NoSQL
Open Source Technology
Ansible
Software Engineering
SQL Databases
Google Cloud Platform
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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