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Staff / Senior Staff Software Engineer - Learned Trajectory Machine Learning Engineer

ZooxFoster City, CA
On-site Full-time

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Experience Level

Mid to Senior

Qualifications

A Master's degree or PhD in Computer Science, Machine Learning, or a related field. Proven experience in machine learning, particularly in deep learning frameworks such as TensorFlow or PyTorch. Strong programming skills in Python and C++. Familiarity with autonomous vehicle technology and motion planning algorithms is highly desirable. Excellent problem-solving abilities and a passion for innovation in the field of machine learning.

About the job

Join our innovative Prediction & Behavior ML team at Zoox, where we are at the forefront of developing cutting-edge machine learning algorithms that analyze and predict driving behaviors from complex data sets. Our algorithms are pivotal in enhancing both on-vehicle driving decision-making and off-vehicle simulation and validation processes. By closely collaborating with the Planner team, we ensure a seamless integration of behavior forecasting and motion planning, driving the advancement of our autonomous vehicle technology. Furthermore, our partnerships with the Perception, Simulation, and Systems Engineering teams enable us to rigorously validate and refine our driving performance.

As a Learned Trajectory Machine Learning Engineer, you will be instrumental in designing and implementing advanced deep learning models that generate accurate trajectories for our vehicles. Your work will directly impact the integration of behavior prediction with motion planning, and you will collaborate extensively with Planner and Perception teams to elevate our vehicle's overall functionality and performance.

About Zoox

At Zoox, we are redefining mobility by designing an autonomous vehicle from the ground up. Our mission is to create a safe and efficient transportation solution that enhances the urban experience. We cultivate a culture of innovation and collaboration, where every team member is empowered to contribute to groundbreaking projects that will shape the future of mobility.

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