Zoox
Senior/Staff Software Engineer - Prediction & Behavior ML
Zoox, Foster City, California, United States, 94420
The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.
In this role, you will:
Develop and apply distributed compute algorithms to efficiently analyze petabytes of urban driving dataDevelop the core metrics that measures performance for our ML modelsWork closely with ML engineers to develop backend metrics and frontend tools for analyzing errors and understanding improvements in our systemsCollaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environmentsQualifications
BS, MS, or PhD degree in computer science or related fieldFluency in C++ or PythonExtensive experience with programming and algorithm designExperience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)Bonus Qualifications
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelinesExperience with latency of analysis and optimization of safety critical software systemsPrior experience with Prediction and/or autonomous vehicles in generalStrong mathematics skillsKnowledge of statistical analysis
CompensationThere are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $210,000 to $300,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.Follow us on LinkedInAccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
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In this role, you will:
Develop and apply distributed compute algorithms to efficiently analyze petabytes of urban driving dataDevelop the core metrics that measures performance for our ML modelsWork closely with ML engineers to develop backend metrics and frontend tools for analyzing errors and understanding improvements in our systemsCollaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environmentsQualifications
BS, MS, or PhD degree in computer science or related fieldFluency in C++ or PythonExtensive experience with programming and algorithm designExperience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)Bonus Qualifications
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelinesExperience with latency of analysis and optimization of safety critical software systemsPrior experience with Prediction and/or autonomous vehicles in generalStrong mathematics skillsKnowledge of statistical analysis
CompensationThere are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $210,000 to $300,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.Follow us on LinkedInAccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
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