Staff Machine Learning Engineer
Watney San Francisco, California, United States
Robotics Engineering · 11-50 employees
Applying here? Try the free cover letter tool — paste this posting and your résumé, no account needed.
About the role
You will own the end-to-end model quality for autonomous robotic systems, including dataset curation, training, and evaluation. Additionally, you will deploy models to production and build systems to ensure low-latency, 24/7 inference on a live fleet of robots.
What they look for
Requirements
Candidates should have experience training large-scale multimodal models on GPU fleets using techniques like video semantic segmentation and 6D pose estimation. Proficiency in Python, PyTorch or JAX, and experience with cluster management systems like Ray or Kubernetes are required.
Full description
Our Mission
Expand human ambition in the physical world.
Critical infrastructure is constrained by labor shortages, hazardous working conditions, and operational complexity. Watney builds and deploys autonomous robotic systems that increase the speed and capacity of buildout, starting with data centers.
About the Role
At Watney, ML engineers turn a live fleet of robots into world class modals. The fleet produces large volumes of video from real work in the field, and turning that data into a model that performs better on the next deployment is one of the hardest problems at the company.
Our Machine Learning team members run training experiments, help curate and label the data behind them, and help evaluate what works on a real fleet. You'll build models that cover the gamut of real world challenges including perception, planning, navigation and manipulation.
What You’ll Do
- Own model quality end-to-end: dataset curation, training, and evaluation.
- Work with multimodal sensor data from Cameras, IMUs, LiDar and Odometry to shape the training set as the fleet grows.
- Train and evaluate policies, experiment with data, feature and architecture ablations.
- Deploy your best results to production and build the systems that guarantee low latency, 24/7 inference on a fleet of robots.
- Work with Teleoperations and Fleet Operations to get the data the models need.
You May Be a Good Fit If You:
- Trained large scale multimodal models on a fleet of GPUs using techniques such as video semantic segmentation, 6d pose estimation, VLAs and BEVs.
- Have owned a dataset end-to-end: what to collect, what to label, and what to cut.
- Write production training and inference code with Python, PyTorch or JAX, Triton.
- Have found and fixed a problem with a training run or a model's real-world performance, and can name the evidence that pointed to it.
- Experience working on Cluster management systems including Ray, Slurm or Kubernetes.
We’re committed to building a diverse, inclusive team. At Watney Robotics, we welcome people of all backgrounds and identities, and we make hiring decisions based on skills, experience, and potential. If you’re passionate about robotics but don’t meet every requirement, we still encourage you to apply!
Curious to learn more?
Follow us here on X and LinkedIn
Similar roles
-
Machine Learning Engineer, AI/ML Model Quality
Apple Cupertino, California, United States
-
Senior Machine Learning Engineer
Coinbase United States · $214K–$225K/yr
-
AIML - Sr Machine Learning Platform Engineer, Evaluation
Apple Seattle, Washington, United States
-
2027 Summer Intern, PhD, Machine Learning - Generative World Models & Controllable Simulation
Waymo Mountain View, California, United States · $177K/yr
-
2027 Summer Intern, Machine Learning, MS/PhD, Simulation Realism (World Model)
Waymo Mountain View, California, United States · $177K/yr
-
Staff Machine Learning Engineer, Offsite Ads
Coupang Mountain View, California, United States · $164K–$282K/yr