Staff Machine Learning Engineer – End to End Autonomy
Woven Planet
full-time
Posted on:
Location Type: Hybrid
Location: Palo Alto • California, Missouri • 🇺🇸 United States
Visit company websiteSalary
💰 $161,000 - $264,500 per year
Job Level
Lead
Tech Stack
PythonPyTorchTensorflow
About the role
- Drive the strategy and development of state-of-the-art initiatives to accelerate end-to-end autonomous driving research, including onboard and offline applications, across Woven and TRI tech leads.
- Identify opportunities, resolve ambiguities, propose initiatives and execute to transfer successful research efforts to the production path.
- Lead the design, development, experimentation and benchmarks of ML models for e2e autonomous driving, ranging from data strategy, multistage training approaches, model selection and experimentation, as well as evaluation methods and deployment.
- Identify opportunities across the training stack and initiate efforts to increase the scalability of ML pipeline to support the training of large foundation models, and to optimize edge deployment needs of sota architectures.
- Collaborate, across timezones, with cross-functional teams such as Data, Perception, Simulation, TRI Research teams to define interfaces and requirements for an end-to-end stack, and to influence technical decisions across the partnership with Woven and TRI to drive innovation.
- Initiate, lead and mentor on ML best practices across teams.
Requirements
- 7+ years of professional experience with machine learning applications or applied science
- MS or higher degree in CS/CE/EE, or equivalent industry experience
- Hands-on experience with recent breakthroughs in generative AI for robotics and/or autonomous driving, such as large e2e behavior models, foundation models, world models, multimodal transformer architectures, pre-training and efficient fine-tuning, LLMs and VLAs.
- Experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred)
- Experience with temporal data and/or sequential modeling
- Familiarity with state-of-the-art architectures for object detection and 3D perception
- Python and C++ experience
- Hands-on experience with large scale distributed training
- Experience in ML workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization
- Knowledge of debugging and profiling deep neural networks on NVIDIA CUDA stack
Benefits
- Excellent health, wellness, dental and vision coverage
- A rewarding 401k program
- Flexible vacation policy
- Family planning and care benefits
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learninggenerative AIlarge e2e behavior modelsfoundation modelsmultimodal transformer architecturespre-trainingefficient fine-tuningtemporal data modelingPythonC++
Soft skills
leadershipmentoringcollaborationproblem-solvingcommunication
Certifications
MS in Computer ScienceMS in Computer EngineeringMS in Electrical Engineering