Software Engineer - ML Infrastructure

The RoleRaydar is recruiting for this role on behalf of our client. Own ML infrastructure across distributed training, reinforcement learning, and production serving. You will establish engineering practices and help researchers translate experiments into reliable systems.What You'll DoBuild distributed training infrastructure with parallelism and checkpointing.Develop reinforcement-learning infrastructure for rollout generation, reward models, and experience collection.Partner with researchers to turn experimental workflows into production systems.Build data loading and preprocessing pipelines for multimodal datasets.Improve model serving, canary deployment, monitoring, and rollout tooling.What We're Looking For6+ years of ML infrastructure or distributed systems experience.Strong Python and hands-on production ML serving experience.Kubernetes and Docker experience with 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, logging, checkpointing, and evaluation.Breadth across the ML infrastructure stack plus technical leadership or mentoring experience.Bonus PointsStartup experience.A/B testing and production ML experimentation platforms.A computer science or other STEM degree.Location And Work ModelSan Francisco, California, United States.Five days per week onsite.Visa transfers and new visa sponsorships are supported.Compensation, As The Posting Describes ItEquity: Competitive equity.