About the job
Be Part of the Future of Home Robotics
At Sunday Robotics, we are pioneering the development of personal robots that alleviate the burden of repetitive household tasks. Our mission is to democratize access to advanced robotics, allowing families to reclaim precious time.
After an intensive 18 months of assembling a talented team, securing funding, and validating our innovative technology, we are eager to welcome passionate individuals to join us as we embark on the next exciting chapter of our journey. If you are enthusiastic about contributing your skills to the cutting edge of robotics, we want to hear from you!
The Role
As a Machine Learning Infrastructure Engineer at Sunday Robotics, you will play a pivotal role in shaping the future of home robotics. You will develop end-to-end machine learning models for robotic manipulation, creating foundational systems that will expedite our efforts to introduce robots into everyday homes.
This versatile position can be customized to align with your specific expertise, whether it be in data pipelines, training infrastructure, or inference. Your contributions will span the entire robot learning pipeline: from ingesting and processing multimodal data to scaling distributed training, optimizing real-time inference, and developing research tools.
What You Will Accomplish
Enhance the research codebase for optimal ergonomics and rapid iteration.
Oversee model training infrastructure, including job scheduling, checkpointing, metrics, and logging.
Facilitate distributed training across GPU clusters with minimal friction for researchers.
Enable the training of larger models through techniques such as sharding and memory optimization.
Profile and enhance GPU utilization, memory efficiency, and training throughput.
Create low-latency inference pipelines for real-time robot control, employing techniques to optimize performance.
Collaborate closely with researchers and roboticists to transform research requirements into robust software and infrastructure.
Data Pipelines and Research Tools
Architect high-throughput pipelines for the ingestion, validation, and transformation of multimodal robot data such as video and proprioception.
Develop efficient storage systems and metadata indexing for seamless data retrieval.

