Machine Learning Engineer

Signature Federal Systems , LLC; Chantilly (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Signature Federal Systems, LLC is seeking a Machine Learning Engineer to design, develop, and deploy AI-driven applications that enhance IT operations and automate processes. You will collaborate with cross-functional teams to deliver insights and scalable ML solutions.

The role emphasizes building ML pipelines, deploying LLMs, and creating robust APIs, with emphasis on maintaining code quality and documentation. Active TS/SCI clearance is required for this position.

Qualifications

• Bachelor's degree in computer science, software engineering, data science, or a related technical field with five years of professional experience.
• Proficiency in Python and object-oriented design, patterns, data structures, and algorithms.
• Experience with Git, Docker, and database management (SQL/NoSQL).
• Knowledge of LLMs, LangChain/LangGraph, and retrieval-augmented generation (RAG).
• Familiarity with vector databases and deploying AI solutions.

Responsibilities

• Develop and maintain ML pipelines and apps using Python and modern ML frameworks.
• Implement and optimize LLM integration and deployment.
• Build RESTful APIs and microservices to serve ML models in production.
• Write clean, well-documented code following OOP principles.
• Collaborate with cross-functional teams to translate requirements into tech solutions.
• Manage training data, model artifacts, and application state with SQL/NoSQL and vector databases.
• Containerize ML apps with Docker for consistent deployment.
• Use Git and participate in code reviews to maintain quality.
• Test and debug ML apps to ensure reliability and accuracy.
• Support deployment and monitoring of AI/ML models in cloud environments.
• Stay updated on ML trends, LLMs, and AI engineering best practices.

Skills

Python

Object-oriented programming

Git

Docker

SQL/NoSQL

LLMs

RAG

Vector databases

LangChain LangGraph

Cloud basics

Education

Bachelor's degree in CS/SE/Data Science

5+ years of software/machine learning experience

Master's degree (desired)

Tools

RESTful APIs

Microservices

Git

SQL/NoSQL databases

LangChain

LangGraph

Job description

Machine Learning Engineer

Location: Chantilly, VA

Clearance Requirement: Active TS/SCI clearance with Polygraph

The Opportunity

Signature Federal Systems is searching for a Software Developer with expertise in artificial intelligence to join its dynamic team. This position centers on developing and implementing AI solutions to strengthen enterprise-level IT operations. The Machine Learning Engineer will collaborate closely with cross-functional teams to design, develop, and deploy AI-driven applications that enhance efficiency, automate processes, and deliver valuable insights.

Duties and Responsibilities

• Develop and maintain machine learning pipelines and applications using Python and contemporary machine learning frameworks.


• Implement and optimize algorithms for integrating and deploying large language models (LLMs).


• Build RESTful APIs and microservices to serve machine learning models in production environments.


• Write clean, maintainable, and well-documented code, adhering to object-oriented programming principles.


• Collaborate with cross-functional teams to understand requirements and convert them into technical solutions.


• Manage training data, model artifacts, and application state using SQL, NoSQL, and vector databases.


• Containerize machine learning applications with Docker to ensure consistent deployment across environments.


• Use Git for version control and participate in code reviews to maintain code quality.


• Conduct testing and debugging of machine learning applications to ensure reliability and accuracy.


• Support the deployment and monitoring of AI and machine learning models in cloud environments.


• Stay up to date with emerging trends in machine learning, LLMs, and AI engineering best practices.

Required Qualifications

• Bachelor's degree in computer science, software engineering, data science, or a related technical field, plus five years of professional experience in software development or machine learning engineering.


• Strong proficiency in Python programming, with a thorough understanding of object-oriented programming 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 large language model technologies, including familiarity with orchestration frameworks such as LangChain and LangGraph.


• Understanding of retrieval-augmented generation (RAG) architectures and vector databases (including ChromaDB, Pinecone, Weaviate, or similar) for building intelligent retrieval systems.


• Strong problem-solving skills, attention to detail, excellent communication abilities, and eagerness to learn within a collaborative team environment.

Desired Qualifications

• Master's degree in computer science or a related field.


• Experience with cloud platforms such as AWS, Azure, or Google Cloud, and knowledge of MLOps practices for machine learning model deployment and monitoring.


• Experience with container orchestration and DevOps, including Kubernetes, Rancher, CI/CD pipelines, and infrastructure automation tools like Ansible.


• Familiarity with enterprise platforms such as ServiceNow, SAP, Tableau, or Splunk.


• Contributions to open-source machine learning projects and familiarity with Agile development methodologies.