Zoox is seeking a Senior Machine Learning Engineer to design and implement advanced perception and detection models for autonomous vehicles using fused sensor data. The role involves training state-of-the-art models, conducting ablation studies, and deploying these models into Zoox's robot fleet. The engineer will collaborate cross-functionally with optimization, data labeling, and planning teams to ensure model performance and successful releases.
- Compensation
- USD 225,000–305,000 / year
What you need
- MS/PhD in Computer Science or related field
- Experience with PyTorch or related ML frameworks
- Experience deploying learned models into production
- Collaboration and teamwork skills
What you will own
- Design and implement cutting-edge detection models using fused sensor data
- Develop joint detection and tracking models and create embeddings for downstream semantic models
- Train ML models, perform studies on State-of-the-Art (SOTA) approaches, and conduct ablations or modifications of existing models
- Document experimental outcomes and drive the deployment of models into Zoox robots
- Visualize data at input and output stages to diagnose issues
- Collaborate with ML optimization, data labeling, metrics, and planner teams for project success
Core skillsPyTorchMachine LearningAutonomous VehiclesComputer VisionDeep LearningPythonData VisualizationCollaboration
Remote policyThe job is listed as 'hybrid,Foster City, CA'.
As a Perception Engineer, you will be instrumental in designing and implementing cutting-edge detection models, utilizing fused sensor data. In particular, the role will be on advanced projects that are aimed at the next generation of driving software, including looking at joint detection and tracking models as well as ways to send rich embeddings to downstream models to relay semantic meaning and capture uncertainty.
This role offers a unique opportunity to directly impact Zoox's expansion into new areas. By developing more generalizable and adaptable models, you will help us navigate diverse and challenging circumstances, accelerating our mission to deliver safe and reliable autonomous mobility. We are looking for a highly motivated individual passionate about pushing the boundaries of perception in the autonomous vehicle space.In this role, you will:
Train ML models, perform various studies into incorporating SOTA approaches as well as ablations/modifications of existing models
Document experimental outcomes and drive towards deploying these models into Zoox robots
Visualize your data at the input and output to understand the issues
Collaborate with teams such as ML optimization, data labeling, metrics and planner to ensure project is successful for Zoox releases
Qualifications
MS/PhD in Computer Science or related field
Experience with PyTorch or related ML frameworks
Experience deploying learned models into production
Excellent collaboration and teamwork skills with proven track record of working on large-scale problems
Bonus Qualifications
Prior experience in the AV or related space with joint detection and tracking models
Deep understanding of how to setup end-to-end training and evaluation processes
Additional
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.
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AccommodationsIf 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.
