
Senior/Staff Machine Learning Engineer, Planning
Plus
full-time
Posted on:
Location Type: Hybrid
Location: Santa Clara • California • United States
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Salary
💰 $130,000 - $220,000 per year
Job Level
About the role
- Use complex map and perception sensor output to develop novel deep learning models for our planning stack.
- Design critical safety checks to ensure driving trajectories are feasible and follow rules of road.
- Ensure all model development keeps a real-time focus and operates efficiently in compute-constrained environments.
- Track and incorporate the latest multidisciplinary research advancements in a fast-moving field.
- Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
- Ensure that technical work meets customer requirements, regulatory standards, and company quality policies.
Requirements
- BS, MS, or PhD in Software, Robotics, or related field
- 4+ years of machine learning engineering experience for robotics applications
- Experience developing high-quality software from design and implementation to testing and deployment.
- Expertise with Python, willingness to do some C++ development as needed.
- Experience training with modern frameworks (e.g. PyTorch)
- A rigorous approach to model development: running well-designed experiments, defining suitable training and validation datasets, and evaluating on the right metrics.
- Hands-on familiarity with cloud data ingestion pipelines
- Strong communication and collaborative skills
Benefits
- Catered free lunch
- Unlimited snacks and beverages.
- Highly competitive salary and benefits package, including 401(k) plan.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
deep learningmachine learningPythonC++software developmentmodel developmentdata ingestion pipelinestestingdeploymentvalidation datasets
Soft skills
communicationcollaborationrigorous approachcontinuous improvementcustomer requirements focus