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Zoox
Foster City, CA, United States
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
Job Source: ZooxZoox
Foster City, CA, United States
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 o
Job Source: ZooxScale AI
San Francisco, CA, United States
Scale’s Foundational ML team conducts research on new foundational capabilities, with the goal of innovating models and algorithms that unlock net-new capabilities for Scale’s applied-ML teams and the broader AI community. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and e
Job Source: Scale AIWaymo
Mountain View, CA, United States
Staff Machine Learning Engineer, Model Optimization Mountain View, California, United States Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to im
Job Source: WaymoWaymo
Mountain View, CA, United States
Staff Machine Learning Engineer, Model Optimization Mountain View, California, United States Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve
Job Source: WaymoSamsung Electronics Perú
Mountain View, CA, United States
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Job Source: Samsung Electronics PerúSamsung Electronics America
Mountain View, CA, United States
Position Summary Role and Responsibilities Samsung Ads is an advanced advertising technology company in rapid growth that focuses on enabling brands to connect with Samsung TV audiences as they are exposed to digital media by using the industry’s most comprehensive data to build the world’s smartest advertising platform. Being part of an internat
Job Source: Samsung Electronics AmericaSamsung Electronics
Mountain View, CA, United States
Position Summary Samsung Ads is an advanced advertising technology company in rapid growth that focuses on enabling brands to connect with Samsung TV audiences as they are exposed to digital media by using the industry’s most comprehensive data to build the world’s smartest advertising platform. Being part of an international company such as Sam
Job Source: Samsung ElectronicsSan Mateo, CA, United States
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.
The Behavior Foundation Model team is responsible for building GPT (Generative Pre-Trained) for autonomous driving and ecosystems for prediction and planning for autonomous driving and offline applications. We're looking for experts in this field to come work with us in building these models and applying them to downstream tasks across the company.
Responsibilities
You will build the foundation models for on-vehicle and offline applications
You will push the boundaries of machine learning in the autonomous driving industry by developing state-of-the-art techniques in self-supervised learning, semi-supervised learning, multi-task learning, and generative models
You will leverage our large-scale machine learning infrastructure to discover new solutions
You will develop new algorithms to model the future behavior of all other agents in the world
You will develop new algorithms to model the future behavior of our own vehicle's future actions, both in predicting our driving trajectories and estimating their quality in relation to our goals of safety, progress, and comfort
You will develop new algorithms to apply generative deep learning to simulation to improve the realism of our offline validation systems
You will engineer software that runs on-vehicle to efficiently execute our algorithms in real time
You will develop metrics and tools to analyze errors and understand improvements of our systems
You will collaborate with engineers on Perception, Prediction, Planning, Simulation, and Systems Engineering to solve the overall Autonomous Driving problem in complex urban environments
Qualifications
BS, MS, or PhD degree in Computer Science or a related field
Fluency with PyTorch, TensorFlow, or JAX
Experience with training and deploying Deep Learning models
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Fluency in Python and a basic understanding of C++
Extensive experience with programming and algorithm design
Strong mathematics skills
Bonus Qualifications
Experience in training of large and complex models
Experience with LLMs
Conference or Journal publications in Machine Learning or Robotics
Prior experience with Prediction and/or Autonomous Vehicles or Robotics in general
Compensation
There 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 $221,000 to $319,000. 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 Zoox
Zoox 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 LinkedIn
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] 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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Email Alert for Senior/Staff Machine Learning Engineer - Foundation Models jobs in San Mateo, CA, United States
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