MakerMaker.AI
MACHINE LEARNING ENGINEER (GENERAL)
San Francisco · On-site · Full-time · Posted Sep 16, 2026
- Experience
- 6+ years building production-grade ML systems.
About the job
Build and own the production ML systems and pipelines that enable research experiments to run reliably at scale, from data and training through evaluation, deployment, and monitoring.
What you'll do
- Build and maintain training, evaluation, and deployment pipelines; take research code from prototype to production.
- Design observability and own training and evaluation data pipelines.
- Work with researchers, set engineering standards, and contribute to architecture decisions.
What they ask for
- 6+ years building production-grade ML systems.
- Experience across the ML lifecycle: data, training, evaluation, deployment, and monitoring; strong distributed systems experience.
- Fluent Python and fluency with at least one of PyTorch or JAX.
- Experience with experimentation infrastructure such as Ray, Slurm, Kubernetes, or similar.
Nice to have
- Experience building experimentation platforms or research infrastructure at a frontier ML lab; background in distributed training systems.
- Open-source contributions to ML infrastructure; experience working effectively with small senior teams.
Tools
Python, PyTorch, JAX, Ray, Slurm, Kubernetes
AI focus
Build ML infrastructure for autonomous research agents and multi-agent systems that propose, run, and analyze machine learning experiments.
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