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.