Staff ML Engineer, Perception, Computer Vision

Our Perception team builds the system that "sees" the world around the self-driving car. We conduct research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale.

In this hybrid role, you will report to a Technical Lead Manager.

You will:

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  Drive the research, design, and implementation of state-of-the-art computer vision and deep learning models for autonomous driving, with a focus on semantic understanding.

  
  
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  Lead the development of novel computer vision algorithms to solve critical real-world perception problems in a safety-critical production environment.

  
  
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  Push the boundaries of computer vision model performance, efficiency, and robustness across diverse operating conditions.

  
  
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  Collaborate with ML infrastructure and Onboard teams to deploy and optimize models on in-vehicle hardware with real-time constraints.

  
  
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  Mentor junior engineers and contribute to the technical vision and roadmap for the Perception team's CV stack.

  
  
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  Stay current with the latest academic and industry research in Computer Vision and Machine Learning and apply relevant findings.

  
  

You have:

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  Master's degree or PhD in Computer Science, Engineering, or a related technical field with a specialization in Computer Vision or Machine Learning.

  
  
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  5+ years of experience in developing and deploying computer vision models in a professional or research setting.

  
  
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  Demonstrated expertise in deep learning frameworks such as PyTorch or TensorFlow/JAX, and strong proficiency in Python and C++.

  
  
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  Proven ability to lead complex technical projects and drive research ideas from conception to production deployment.

  
  
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  Deep understanding of modern computer vision architectures and their practical application.

  
  
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  Experience with large-scale data, model training, and evaluation pipelines for computer vision tasks.

  
  
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  Strong communication and collaboration skills in a fast-paced, cross-functional environment.

  
  

We prefer:

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  Experience in the autonomous vehicle (AV) or robotics industry, particularly with real-time on-device perception systems.

  
  
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  Proven track record of publications at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS).

  
  
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  Experience with Multi-Modal Large Language Models (MLLMs), diffusion models, and advanced reasoning techniques.

  
  
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  Experience with model optimization techniques such as quantization, pruning, or knowledge distillation.

  
  
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  Familiarity with distributed training and inference optimization on GPU/TPU clusters.