Senior Machine Learning Engineer, Public Sector
$196k - $294k • Denver, CO; Honolulu, HI; Washington, DC
Posted 5d ago
Job Location
Denver, CO; Honolulu, HI; Washington, DC
Tech Stack
Remote Work Policy
On-site
Categories
Machine Learning Engineer
About the job
Scale is seeking a Senior Machine Learning Engineer to own the application of generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical production problems. In this role, you will tackle challenges without established solutions, proposing and building architectures, and ensuring their performance in customer-dependent environments. The Public Sector Machine Learning team focuses on deploying advanced models to government systems, with a primary emphasis on agentic systems built on large language models. This includes developing agents for complex operational and planning tasks, integrating retrieval pipelines and production APIs, managing state for long-running tasks, performing geospatial reasoning, and creating evaluation tooling. The role also involves applying reinforcement learning and computer vision for defense applications, including evaluation, labeling efficiency, and multimodal model training. As a Senior MLE, you will have design authority over a capability area, making final decisions on team patterns and ensuring they function under real-world constraints like classified environments, limited compute, and strict correctness requirements.
Responsibilities
- Own the design and delivery of agent capabilities end-to-end, including architecture, implementation, and evaluation.
- Define and propose new patterns for problem spaces lacking established approaches, leading their development.
- Deploy state-of-the-art internal and community models into production to address customer needs.
- Maintain and improve production models and agents through retraining, tuning, and architectural updates.
- Build agent-level evaluation benchmarks, LLM judges, and verifiers to enhance performance.
- Collaborate with product and research teams to define high-impact initiatives.
- Develop scalable machine learning infrastructure to automate and optimize ML services.
- Engage directly with government users and subject-matter experts to inform technical direction.
- Act as a mentor and primary reviewer for the team, assisting the manager with feasibility assessments.
- Clearly communicate technical tradeoffs to non-technical stakeholders.
- Integrate security and compliance as fundamental design constraints.
- Represent and advocate for machine learning techniques across engineering and product organizations.
- Quickly learn new technologies and manage multiple priorities in a fast-paced setting.
- Be comfortable with light travel for customer interaction and team needs.
Requirements
- 5+ years of experience building and deploying applied ML systems in production.
- Extensive experience with GenAI, Agentic AI, NLP, deep learning, deep reinforcement learning, or computer vision in production.
- Proven track record of owning architectural decisions and defending tradeoffs.
- Experience shipping agentic systems with real production traffic and rigorous evaluation.
- Solid background in algorithms, data structures, and object-oriented programming.
- Strong programming skills in Python.
- Experience with PyTorch or TensorFlow.
- Experience mentoring or reviewing the work of other engineers.
Benefits
- Base salary
- Equity
- Benefits
- Compensation packages include base salary, equity, and benefits.
- Equity based compensation