Raydar
Software Engineer - ML Infrastructure
$250K–$300K
San Francisco, California · Full-time · Posted Sep 19, 2026
- Experience
- 6+ years of ML infrastructure or distributed systems experience.
- Visa sponsorship
- Visa transfers and new visa sponsorships are supported.
About the job
Own ML infrastructure for distributed training, reinforcement learning, data pipelines, and production model serving, while helping researchers turn experiments into reliable systems.
What you'll do
- Build distributed training and reinforcement-learning infrastructure, including parallelism, checkpointing, rollout generation, and experience collection.
- Partner with researchers to productionize experimental workflows and build multimodal data loading and preprocessing pipelines.
- Improve model serving, canary deployment, monitoring, and rollout tooling.
What they ask for
- Strong Python and hands-on production ML serving experience.
- Kubernetes and Docker experience, including GPU scheduling, autoscaling, and reproducible environments.
- Distributed training expertise in PyTorch or JAX, including FSDP, DeepSpeed, or comparable approaches; experience with RL or online-learning loops.
- Breadth across the ML infrastructure stack plus technical leadership or mentoring experience.
Nice to have
- Startup experience.
- A/B testing and production ML experimentation platforms; a computer science or other STEM degree.
Pay
USD 250,000 to 300,000 per year (base salary)
Tools
Python, Kubernetes, Docker, PyTorch, JAX, FSDP, DeepSpeed
AI focus
Build and operate infrastructure for machine learning systems, including distributed training, reinforcement learning, and production serving for clinical applications.
Model-written summary · the original posting is authoritative