Contribute to CI/CD, observability, and operational support for AI systems in secure environments
Support responsible AI and model governance practices, including explainability and compliance requirements
Document architectures, workflows, and engineering standards for project delivery
What You Will Need
Level and Compensation: This position may be filled at multiple career levels based on business need and the selected candidate's qualifications, relevant experience, and demonstrated capability. Typical leveling for this role is as follows:
Junior (0 to 4 years)
Mid-Level (5 to 9 years)
Senior (10 to 14 years)
Principal (15 or more years)
These ranges are guidelines only and are not the sole determining factor in level. The posted compensation range reflects the full range across all possible levels. Individual offers will be based on the level at which the candidate is hired, as well as factors such as skills, experience, internal equity, and geographic market considerations where applicable.
Education and Experience
Bachelor's degree in Computer Science, Data Science, Software Engineering, Engineering, or a related technical field; Master's degree preferred
Relevant professional experience in AI engineering, machine learning engineering, or related software engineering roles; the depth and scope of experience required will vary based on the level at which this position is filled
Experience deploying or supporting machine learning and AI systems in production environments preferred
Experience working in cloud-based or hybrid technical environments preferred
Knowledge, Skills, and Abilities
Proficiency in Python
Familiarity with frameworks such as TensorFlow, PyTorch, and scikit-learn
Familiarity with MLOps, CI/CD for ML, and model monitoring concepts and practices
Exposure to LLMOps, AIOps, RAG, and vector databases
Experience building or supporting data pipelines for AI/ML applications
Understanding of software engineering and DevSecOps practices for production systems
Strong collaboration skills across technical teams and stakeholders
Nice to Have
Experience supporting production ML at scale
Experience with AWS, Azure, or GCP AI/ML services
Familiarity with federal, public sector, or regulated AI environments
Exposure to NLP, classification, survey analytics, or entity resolution use cases
Location
This position is based in the Washington, D.C. metro area, with primary work performed in Suitland, Maryland. Remote or hybrid arrangements may be available for eligible work, subject to government approval.
Notice: This role has been opened for a future need expected within three months of the original posting date of this position. Potential candidates may not receive communication until the open headcount is confirmed.
