Senior Machine Learning Engineer, Public Sector

Sourced from justjobs.com

Scale AI is hiring a Senior Machine Learning Engineer for its Public Sector team to deploy generative AI, agentic AI, computer vision, and reinforcement learning into mission-critical government systems. You will own the design and delivery of agent capabilities end to end, from architecture through evaluation, working under real constraints like classified environments and limited compute. The role requires an active TS security clearance and close collaboration with government users and subject-matter experts.

• Own the design and delivery of agent capabilities end to end, including architecture, implementation, and evaluation
• Define net-new patterns in problem spaces with no established approach and lead their implementation
• Put state-of-the-art internal and community models into production for customers
• Improve and maintain production models and agents through retraining, tuning, and architectural updates
• Build agent-level evaluation benchmarks, LLM judges, and verifiers to hillclimb performance
• Build scalable machine learning infrastructure to automate and optimize ML services
• Work directly with government users and subject-matter experts to translate insights into technical direction
• Mentor and review the work of other engineers
• Communicate technical tradeoffs to non-technical stakeholders
• Treat security and compliance as design constraints

• 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
• Track record of owning architectural decisions and defending tradeoffs
• Experience shipping agentic systems with real production traffic and evaluation rigor
• Solid background in algorithms, data structures, and object-oriented programming
• Strong Python skills and experience with PyTorch or TensorFlow
• Experience mentoring or reviewing other engineers
• Active TS security clearance

• Graduate degree in Computer Science, Machine Learning, or AI
• Experience with cloud platforms such as AWS or GCP
• Experience with computer vision, generative AI models, LLMs, or agentic systems
• Familiarity with ML evaluation frameworks and agentic model design
• Experience deploying ML in classified, air-gapped, or IL5+ environments
• Geospatial or GEOINT experience
• Inference optimization experience
• Fine-tuning experience with SFT, RL, or embedding models