Skip to content

Senior Machine Learning Engineer – Motion Planning
Company | Woven |
---|
Location | Palo Alto, CA, USA |
---|
Salary | $140000 – $230000 |
---|
Type | Full-Time |
---|
Degrees | Master’s |
---|
Experience Level | Senior |
---|
Requirements
- MS, or higher degree, in Machine Learning, Robotics, Computer Science, Computer Engineering (or other related fields)
- 5+ years of experience with ML frameworks such as PyTorch, Caffe, Tensorflow
- Extensive experience with learning-based planning approaches like imitation learning, reinforcement learning and state-of-the-art techniques for sequential modeling like Transformer architectures, and camera input or vector/point-based representations
- Strong programming skills in Python or C++
- 5+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization
- Passionate about self driving car technology and its potential for humanity
- Strong communication skills and ability to communicate concepts clearly and precisely
Responsibilities
- Motion Planning ML model R&D by prototyping, validating and iterating on existing and new model architectures leveraging imitation learning, deep reinforcement learning, and large-scale data
- Own development of new ML models end-to-end from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on road performance
- Lead large, multi-person projects and significantly influence the overall Motion Planning architecture and technical direction
- Enable and help other engineers on the team to be more effective through coaching and leading by example when it comes to writing high-quality code, providing high-quality code and design document reviews and delivering rigorous reports from ML experiments
- Work in a high-velocity environment and employ agile development practices
- Team player and ‘get things done’ mentality
- Collaborate closely with teams such as Perception, Simulation, Infrastructure, Tooling to drive unified solutions
- Closely collaborate with Motion Planning subteams to develop end-to-end solutions
Preferred Qualifications
- Experience with robot motion planning techniques like trajectory optimization, sampling-based planning, model predictive control, etc or self-driving problems (Perception, Prediction, Mapping, Localization, Planning, Simulation)
- Experience in writing production level code in a real-time operating system
- Experience with temporal/sequential modeling and/or reinforcement learning
- Experience in optimizing runtime-critical systems for Linux, UNIX-like real-time operating systems on automotive-grade compute platforms, and building safety-critical software architecture