Zoox
Senior/Staff Machine Learning Engineer, Agent Simulation
Zoox, Foster City, California, United States, 94420
The Agent Simulation group at Zoox is in search of machine learning engineers to play a crucial role in enhancing agent behaviors, assessing performance, and developing tools to prioritize simulation results. You will be instrumental in the development of reliable and validated simulations, and have the opportunity to work with a wealth of real-world driving data and an exceptional infrastructure for testing and validating your algorithms. Our ML group is focused on creating diverse and innovative agent behaviors, and your contributions will be key in this endeavor.
In this role, you will:
Research, implement, and optimize state-of-the-art machine learning approaches to improve plausible agent behaviorsFind innovative solutions for agent behaviors and simulation analysisProve machine-learned algorithms have better performance than heuristicsLeverage our large-scale machine-learning infrastructure to discover new solutionsAnalyze the difference between behaviors in simulation and real-worldWork cross-functionally with our safety and autonomy engineersBuild scalable, usable cloud pipelines for machine learning solutions for simulationQualifications
BS, MS, or PhD degree in Computer Science or a related fieldExperience with training and deploying deep learning modelsExperience with production machine learning pipelines: dataset creation, training frameworks, metrics pipelinesFluency in Python and a basic understanding of C++Fluency with Numpy and PyTorch, TensorFlow or JAXStrong mathematics skillsBonus Qualifications
Experience with LLMs, reinforcement learning, imitation learningConference or journal publications in machine learning or roboticsPrior experience with agent behaviors, prediction, autonomous vehicles or robotics
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 $200,000 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:
Research, implement, and optimize state-of-the-art machine learning approaches to improve plausible agent behaviorsFind innovative solutions for agent behaviors and simulation analysisProve machine-learned algorithms have better performance than heuristicsLeverage our large-scale machine-learning infrastructure to discover new solutionsAnalyze the difference between behaviors in simulation and real-worldWork cross-functionally with our safety and autonomy engineersBuild scalable, usable cloud pipelines for machine learning solutions for simulationQualifications
BS, MS, or PhD degree in Computer Science or a related fieldExperience with training and deploying deep learning modelsExperience with production machine learning pipelines: dataset creation, training frameworks, metrics pipelinesFluency in Python and a basic understanding of C++Fluency with Numpy and PyTorch, TensorFlow or JAXStrong mathematics skillsBonus Qualifications
Experience with LLMs, reinforcement learning, imitation learningConference or journal publications in machine learning or roboticsPrior experience with agent behaviors, prediction, autonomous vehicles or robotics
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 $200,000 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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