Summary
What you’ll impact
The Machine Learning Engineer on the organization's Public Sector team will develop and deploy generative AI, LLM, and computer vision models for mission‑critical government systems. They will work with massive datasets, build scalable infrastructure, and collaborate across product and research groups to deliver ML‑driven enhancements.
Responsibilities
What you'll do
- Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
- Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
- Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
- Work with massive datasets to develop both generic models as well as fine tune models for specific products
- Build scalable machine learning infrastructure to automate and optimize our ML services
- Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
- Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
- Comfortable with light travel (approximately 10%) for customer interaction and team needs
Requirements
What you’ll bring
- This role will require an active TS security clearance
- 2+ years of experience building and deploying applied ML systems in production environments
- Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
- Solid background in algorithms, data structures, and object-oriented programming
- Strong programming skills in Python, experience in Tensorflow or PyTorch