ML Engineering Manager — Perception, Robotics & MLOps

Mariana Minerals; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Mariana Minerals seeks a Machine Learning Engineering Manager to lead ML engineers in perception, robotics, and agentic workflows. You will guide the ML platform and MLOps stack, hire and develop talent, and align with Technical Product Managers on what to build and why.

You will balance hands-on work with strategic direction, ensuring reliability and coherence across growing use cases in our industrial AI environment.

Qualifications

• 6+ years in ML engineering, including 2+ years managing ML engineers.

Responsibilities

• Manage, coach, and grow a team of ML engineers across perception, robotics, agentic workflows, and ML platform; hiring, onboarding, performance reviews, career development.
• Own the technical direction of the team: architecture, deployment readiness, and when to push features to production.
• Partner with TPMs on roadmap; translate priorities into scoped engineering work and manage feasibility.
• Own the ML platform and MLOps stack as a product used across the ML org, including training, evaluation, deployment, and monitoring.
• Own engineering practices for perception and robotics: data collection, evaluation on plant conditions, safety and fallback behavior.
• Own engineering practices for LLM and agentic tools: evaluation, guardrails, cost, latency.
• Maintain seam with software engineering organization for shared infrastructure and interfaces.
• Oversee production lifecycle: deployment, monitoring, incident response, on-call reliability.

Skills

People leadership

Machine learning

Production ML systems

Vision/Perception

LLM/Agentic workflows

ML platform/MLOps

Cross-functional collaboration

Tools

ML Platform

MLOps

Job description

Mariana Minerals seeks a Machine Learning Engineering Manager to lead ML engineers in perception, robotics, and agentic workflows. You will guide the ML platform and MLOps stack, hire and develop talent, and align with Technical Product Managers on what to build and why.

You will balance hands-on work with strategic direction, ensuring reliability and coherence across growing use cases in our industrial AI environment.