Zoox
Autonomous Vehicles
MachineLearningEngineerSemanticReasoning(Highway)
“Machine Learning Engineer - Semantic Reasoning (Highway) at Zoox. Skills: Semantic Reasoning, Deep Learning, Autonomous Vehicles, Machine Learning. Design, train, and deploy deep learning models. Adapt and elevate unified machine learning stack”
What You'll Achieve.
Achieve extended spatial range and high fidelity for highway environments; Ensure model outputs meet strict safety and clearance metrics; Ensure low-latency execution; Ensure vehicles remain safe and resilient
Industry & Context.
Tackle unpredictability of urban driving; Resolve perception-related regressions and edge cases
Work within rigorous compute constraints of the Zoox vehicle platform
What They're Looking For.
Must Have
MS (3–5 years) or PhD (0–2 years) in Computer Science, Robotics, Electrical Engineering, or a related field, professional software engineering experience, Deep understanding of 2D/3D computer vision, semantic segmentation, deep learning architectures, Exceptional programming skills in modern C++, Python, Hands-on experience with modern deep learning frameworks like JAX or PyTorch, Proven track record of deploying real-time machine learning models on resource-constrained embedded systems or on-bot hardware
Nice to Have
Prior experience dealing with highway autonomous driving scenarios and their specific mapping/perception challenges, Familiarity with state-of-the-art, BEV, Sparse Transformer architectures, Vision-Language Models (VLMs), publication record in top AI conferences or journals (e. g. , CVPR, ICCV, ECCV, ICML, NeurIPS)
What You'll Do.
and deploy deep learning models
Adapt and elevate unified machine learning stack
Define semantic representation requirements
Establish robust validation workflows
Optimize deep learning models for real-time inference
Investigate and resolve perception-related regressions
Contribute to long-term architecture
How You'll Work.
Team & Collaboration
Collaborate with partner Perception and motion planning teams; Collaborate with Scene Intelligence, Semantic Grounding, and PCP Mapping teams; Partner with downstream motion planning teams
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