ML Infrastructure Engineer

Design high-throughput pipelines for ingesting, validating, and transforming multimodal robot data (video, proprioception, actions)

Build storage systems and metadata indexing for efficient dataset management at large scale

Optimize dataloaders, sharding and prefetching to minimize time from data arrival to model training

Build research tooling for debugging, visualization and experiment analysis

Strong software engineering and systems fundamentals

Experience building distributed systems or large-scale data pipelines

Hands-on experience with ML training infrastructure, ideally PyTorch

Comfort reasoning about performance, memory, I/O, and GPU utilization

Experience managing training workloads (SLURM, Kubernetes, or similar)

Ownership mindset: you design, build, operate, and iterate on systems end-to-end

Enjoy working closely with researchers and unblocking fast-moving projects

Experience with robotics data pipelines or multimodal models

Background in VLAs, Video Generation architectures or robot learning systems

Deep ML systems experience: training compilers, custom kernels, runtime optimization

Hands-on GPU performance tuning

Experience with serialization formats for high-performance systems (Protobuf, FlatBuffers, MCAP)

At Sunday Robotics, we’re building technology shaped by real people — curious, creative, and diverse. We’re proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Even if you don’t meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria — we don’t want that to be the reason we miss out on great talent.