Strong foundation in machine learning concepts, including model selection, training, validation, and evaluation
Experience building and deploying ML models in real-world applications
Proficiency in Python and common ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)
Experience working with large language models, embeddings, and prompt-driven systems
Familiarity with data processing tools and workflows (e.g., Pandas, SQL, Spark, or similar)
Understanding of software engineering best practices (version control, testing, code reviews)
Ability to reason about tradeoffs between accuracy, latency, cost, and maintainability
Strong communication skills and comfort working in cross-functional teams
Performs other related duties as assigned
Applicants must be authorized to work in the United States. In alignment with federal contract requirements, certain roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or a security clearance
Experience working in innovation, R&D, labs, or exploratory engineering teams
Experience deploying models to cloud platforms and managing inference at scale
Familiarity with MLOps practices such as model monitoring, CI/CD for ML, and experiment tracking
Experience contributing to architectural discussions or technical strategy
Location: Hybrid/Remote. Candidates must be located in the DMV area (DC, Maryland, Virginia) and able to participate with in-office collaboration