Perform rapid diagnosis across model, data, code, infrastructure, and evaluation layers for blocked or unstable efforts.
Identify root causes and define corrective actions required to restore progress.
Communicate findings and resolution plans clearly across research, engineering, and operational teams.
Contribute directly to blocked ML initiatives by implementing fixes across model behavior, data pipelines, and system architecture.
Develop and validate solutions, including debugging, targeted refactoring, and experimental validation.
Ensure that resolved systems are stable, validated, and ready for continued development.
Provide clear handoff artifacts, including working code, documentation, and recommended next steps.
Work across research, infrastructure, platform, evaluation, and integration teams to align on root causes and resolution plans.

Senior-level experience spanning software engineering, machine learning systems, and infrastructure in production or production-adjacent environments.
Solid debugging capability across multiple system layers, including application code, data pipelines, distributed training, and deployment systems.
Experience diagnosing and resolving complex issues in ML systems under time constraints.
Well-developed operational judgment, including the ability to triage, prioritize, and execute with incomplete information.
Effective communication skills and ability to collaborate across multiple technical disciplines.

Senior Tactical ML Engineer

Key skills