Description
The goal of a Senior Machine Learning Engineer at Scale is to own the application of generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical problems in production.
Our Public Sector Machine Learning team focuses on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. The team's primary focus is on agentic systems built on large language models, developing agents that solve complex operational and planning challenges for government partners.
As a Senior MLE, you'll have design authority over a capability area, proposing architectures, building them with support from other engineers, and being accountable for their performance in customer-dependent environments.
Responsibilities:
- Own the design and delivery of agent capabilities end-to-end, including architecture, implementation, and evaluation.
- Define new patterns in problem spaces with no established approach and lead the work to build them.
- Put state-of-the-art models into production to solve customer problems.
- Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates.
- Build agent-level evaluation benchmarks and use them to improve performance.
- Partner with product and research teams to scope high-impact initiatives.
- Build scalable machine learning infrastructure.
- Work directly with government users and subject-matter experts.
- Act as a force multiplier and primary reviewer for your team.
- Communicate technical tradeoffs clearly to non-technical stakeholders.
- Treat security and compliance as design constraints.
- Serve as a cross-functional representative for machine learning techniques.
- Be comfortable learning new technologies quickly and managing multiple priorities.
- Comfortable with light travel (approximately 10%) for customer interaction and team needs.
Requirements:
- Active TS security clearance.
- 5+ years of experience building and deploying applied ML systems in production environments.
- Extensive experience with GenAI, Agentic AI, NLP, deep learning, and computer vision.
- Track record of owning architectural decisions.
- Experience shipping agentic systems with real production traffic.
- Solid background in algorithms, data structures, and object-oriented programming.
- Strong programming skills in Python, experience in PyTorch or Tensorflow.
- Experience mentoring or reviewing engineers.
Nice to Haves:
- Graduate degree in Computer Science, Machine Learning, or Artificial Intelligence.
- Experience working with cloud platforms and deploying ML models in cloud environments.
- Experience with computer vision, generative AI models, large language models, or agentic systems.
- Familiarity with ML evaluation frameworks and agentic model design.
- Experience deploying ML in classified environments.
- Geospatial or GEOINT experience.
- Inference optimization experience.
- Fine-tuning experience.
Benefits:
- Comprehensive health, dental, and vision coverage.
- Retirement benefits.
- Learning and development stipend.
- Generous PTO.
- Commuter stipend.
Salary Range:
The base salary range for this full-time position in Washington DC is: $235,200-$294,000 USD