Raydar
Machine Learning Infrastructure Engineer
$200K–$300K
San Francisco, California · Full-time · Posted Oct 12, 2026
- Experience
- 3+ years of experience in machine learning infrastructure.
About the job
Own and scale the production infrastructure for training and serving machine learning models, improving reliability, latency, observability, and cost.
What you'll do
- Operate and enhance production model-prediction systems and training environments.
- Build logging, metrics, alerting, data pipelines, and tools to move research models into production.
- Design multi-cloud workload infrastructure that balances quality, response time, and cost.
What they ask for
- Proven experience operating production model-deployment systems in a demanding engineering team.
- Strong Python skills and systems engineering experience with Kubernetes.
- Expertise diagnosing GPU performance limits, tuning model deployment, and monitoring.
- Comfort working in a fast-paced startup environment.
Nice to have
- Hands-on training and deployment experience on a small number of machines.
- Technical degree from a leading program, research publications, open-source contributions, or strong competition results.
Pay
USD 200,000 to 300,000 per year (base salary)
Tools
Python, Kubernetes
AI focus
Infrastructure for training, deploying, and running machine learning models in production.
Model-written summary · the original posting is authoritative