Nimble Robotics
Senior/Staff Software Engineer, Infrastructure (ML)
$210K–$300K
San Francisco, CA +1 · Staff · Full-time · Posted Aug 18, 2026
- Location
- San Francisco, CA
San Francisco, California, United States - Experience
- 4+ years of industry experience in infrastructure, distributed systems, ML systems, robotics, or a related area.
- Education
- Bachelor’s, Master’s, or PhD in Computer Science or a related field, or equivalent practical experience.
About the job
Build and scale ML training infrastructure and low-latency inference systems for Nimble’s warehouse robots.
What you'll do
- Design and maintain infrastructure for efficient ML training, experiment management, and distributed data processing.
- Build production inference pipelines and develop, tune, and optimize CUDA kernels.
- Lead or participate in design reviews, review code, document systems, and mentor junior engineers.
What they ask for
- Experience with Rust, Go, Python, or C++; and with PyTorch or JAX.
- Strong understanding of distributed systems, systems programming, memory management, and performance optimization.
- Experience with Kubernetes orchestration, resource scheduling for large distributed jobs, and containerized deployment pipelines.
- Ability to debug and optimize GPU, networking, filesystem, and multi-GPU bottlenecks.
Nice to have
- Hands-on experience with distributed training frameworks or techniques such as PyTorch DDP/FSDP, DeepSpeed, Megatron, or NCCL; or GPU kernel development.
- Experience with data engineering technologies such as Parquet or Arrow.
Pay
$210,000 and $300,000/year (base salary)
Tools
Rust, Go, Python, C++, PyTorch, JAX, Kubernetes, CUDA
AI focus
Build training and inference systems for general-purpose warehouse robots, including distributed model training and production robotics workloads.
Model-written summary · the original posting is authoritative