ML Infrastructure Engineer (Robotics)

Location: Redwood City, California, United States; on-site

Company

hirify.global is developing personal home robots and end-to-end machine learning models for robot manipulation.

What you will do

• Maintain research software and infrastructure for fast, reliable experimentation.
• Build and operate model-training infrastructure, including scheduling, checkpointing, metrics, logging, and distributed GPU training.
• Optimize training performance through sharding, activation checkpointing, memory optimization, and GPU utilization profiling.
• Develop low-latency inference pipelines for real-time robot control using quantization, distillation, and model compilation.
• Design high-throughput pipelines and storage systems for multimodal robot data, including video, proprioception, and actions.
• Build tooling for dataset management, debugging, visualization, and experiment analysis while collaborating with researchers and roboticists.

Requirements

• Strong software engineering and systems fundamentals.
• Experience building distributed systems or large-scale data pipelines.
• Hands-on experience with machine learning training infrastructure, ideally PyTorch.
• Understanding of performance, memory, I/O, and GPU utilization.
• Experience managing training workloads with SLURM, Kubernetes, or similar systems.
• Ability to design, build, operate, and iterate on systems end to end.

Nice to have

• Experience with robotics data pipelines or multimodal models.
• Background in VLAs, video generation architectures, or robot learning systems.
• Experience with training compilers, custom kernels, runtime optimization, or GPU performance tuning.
• Experience with Protobuf, FlatBuffers, MCAP, or other high-performance serialization formats.

Culture & Benefits

• Work with a curious, creative, and diverse team building home robotics technology.
• Equal opportunity employment for qualified applicants.
• Encouragement to apply even when not every listed requirement is met.