Sunday (sunday.ai)
ML Infrastructure Engineer
Redwood City, CA
Sponsorship not specifiedDetected 161 days ago
Distributed SystemsKubernetesMachine LearningPyTorchData EngineeringRoboticsResearch
About the role
- This is a broad role that can be tailored to your specific area of expertise: data pipelines, training infrastructure or inference.
Responsibilities
- Maintain an effective research codebase with good ergonomics, optimizing for fast iteration and correctness
- Own infrastructure for model training: job scheduling, checkpointing, metrics, and logging
- Profile and optimize gpu utilization, memory usage and training throughput
- Build low-latency inference pipeline for real-time robot control, apply quantization, distillation and model compilation to optimize inference performance
- 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
Requirements
- 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)
Nice to have
- Experience with robotics data pipelines or multimodal models
- 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)
- 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.
Company info
- What We're Looking For
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