ML Engineering Manager: Perception, Robotics & MLOps Lead

Mariana Minerals; Ann Arbor (MI); On-site; USD 150,000 - 230,000; Full time

Job summary

Mariana Minerals is seeking a Machine Learning Engineering Manager to lead the ML engineers working on perception and robotics, agentic workflows, and the ML platform and MLOps infrastructure across the applied AI/ML organization.

You will build a strong team of generalists, maintain platform coherence as use cases grow, and partner with Technical Product Managers — ML & Robotics, and Data & Analytics Platform — on what gets built and why.

Qualifications

• 6+ years in machine learning engineering, including 2+ years managing ML engineers with direct responsibility for hiring, performance, and growth.
• Hands-on track record shipping ML systems to production in at least two of: computer vision / perception, robotics or embedded ML, LLM-powered or agentic applications, ML platform / MLOps infrastructure.
• Strong software engineering fundamentals: you've built and operated production systems, you care about interfaces and reliability, and you can hold a design review with software engineers as a peer.
• Working fluency with the current LLM/foundation-model landscape — what the models can do today, how to evaluate them, and where agentic approaches genuinely fit versus conventional software.
• Track record of setting technical direction for a team and delivering against commitments in an ambiguous, cross-functional environment.
• Ability to evaluate work you didn't do — you can review a model, a pipeline, or a system design and give feedback that makes the engineer better.
• Exceptional written and verbal communication across audiences, from ML engineers to operators to executives.

Responsibilities

• Manage, coach, and grow a team of ML engineers across perception, robotics, agentic workflows, and ML platform — hiring, onboarding, 1:1s, performance reviews, career development, and the hard conversations when they're needed.
• Own the technical direction of the team: which approaches to bet on, how the platform is architected, and what "good enough to deploy" means for a vision model, a robot, or an agent.
• Partner with TPMs on the roadmap: translate product priorities into scoped engineering work, push back when the ask isn't feasible, and commit to what the team will deliver.
• Own the ML platform and MLOps stack as a product the rest of the ML org uses: training infrastructure, evaluation, deployment, monitoring, and the paved road that lets every MLE ship faster.
• Own the engineering practices for perception and robotics: data collection and labeling, evaluation on real plant conditions, safety and fallback behavior, and the path from a demo to a system operators trust.
• Own the engineering practices for LLM and agentic tools: evaluation, guardrails, cost, latency, and the discipline to know when an agent is the right answer and when conventional software is.
• Own the seam with the software engineering organization at the engineering level — shared infrastructure, interfaces, and ownership — so nothing falls in the gap between the two orgs.
• Own the production lifecycle of the team's systems — deployment, monitoring, incident response, on-call — and the reliability bar for systems that act in a plant.
• Stay hands-on enough to review the hardest work, unblock engineers, and prototype when the fastest path to an answer is to build it yourself.
• Own headcount planning and hiring for the team, and build a pipeline of ML engineers who can move between problem areas.

Job description

Mariana Minerals is seeking a Machine Learning Engineering Manager to lead the ML engineers working on perception and robotics, agentic workflows, and the ML platform and MLOps infrastructure across the applied AI/ML organization.

You will build a strong team of generalists, maintain platform coherence as use cases grow, and partner with Technical Product Managers — ML & Robotics, and Data & Analytics Platform — on what gets built and why.