Lead Machine Learning Engineer

5 days ago

Sonoma, CA, United States Strativ Group Full time

Lead Machine Learning Engineer - Agentic Systems

Join a cutting-edge AI research company dedicated to developing advanced AI systems that can navigate complex, real-world engineering challenges. As a well-funded organization executing large-scale projects, we're at the forefront of creating AI systems that reason, plan, and act reliably in physical environments.

Our platform is engineered to empower intelligent agents to accomplish comprehensive engineering workflows by integrating large language models with structured planning, deterministic execution, and real system constraints. This role is positioned at the intersection of AI research, systems engineering, and applied infrastructure, prioritizing safety, reproducibility, and first-principles design. Our team comprises highly skilled engineers and researchers with diverse expertise in ML systems, distributed infrastructure, and applied AI, working in a high-ownership environment where you'll design and deploy foundational systems that enable innovative classes of agentic behavior.

We are seeking a Lead ML Engineer to develop and construct the core planning and orchestration frameworks that facilitate LLM-based agents in reliably performing multi-step engineering tasks. You will collaborate closely with systems, data, and ML teams to seamlessly integrate agent workflows into actual production toolchains. This position offers significant technical ownership and the chance to influence how intelligent agents interact with complex systems on a large scale.

What You'll Be Working On

  • Designing and implementing innovative agent planners, orchestration workflows, and state machines using contemporary agent frameworks
  • Creating deterministic tool-calling pipelines with standardized schemas and clear execution pathways
  • Developing action adapters and cross-tool interfaces to ensure safe and reproducible agent behavior
  • Implementing robust error management strategies, including retries, timeouts, rollbacks, and replay mechanisms
  • Collaborating with systems architecture, data infrastructure, and ML teams to deploy agents in real engineering environments

Essential Experience Required

  • Extensive experience in building agent systems, LLM orchestration frameworks, or structured tool-calling pipelines
  • Strong understanding of schemas, action abstractions, deterministic execution, and reproducibility
  • Experience in analyzing system-level failure modes, edge cases, and facilitating safe tool interactions
  • Comfort in working across AI models, systems engineering, and domain-specific tools
  • A builder's mindset with a passion for tackling ambiguous problems, utilizing first-principles design, and owning systems from start to finish

Above all, we are in search of engineers who show outstanding technical depth, strong ownership, and the capability to develop reliable agent systems under real-world constraints. We encourage you to apply as soon as possible if you're excited about this opportunity.

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