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Waymo is looking to solve the problem of improving access to mobility while saving thousands of lives lost to traffic crashes by developing and deploying state-of-the-art machine learning solutions for its autonomous driving technology

Requirements

• Coding and testing skills, specifically Python/C++
• Familiarity with large-scale fleet management, testing, and deployment, e.g.: GCP/AWS/Kubernetes, Jenkins, GCS/S3, etc.
• Familiarity with large-scale MLOps tools, e.g.: tf.serving/Torchserve, Kubeflow/Sagemaker Pipelines/Vertex AI Pipelines, etc.
• Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow
• 7+ years building and maintaining high-scale distributed or ML inference systems
• B.S. in Computer Science, Math, or equivalent real-world experience

Responsibilities

• Collaborate with data scientists, engineers, and other stakeholders to deploy machine learning models into production
• Develop and maintain CI/CD pipelines for automating data generation, model training, testing, and deployment processes
• Implement best practices for model versioning, monitoring, and governance
• Troubleshoot and resolve issues related to model deployment and performance
• Stay current with emerging technologies and trends in ML Ops and DevOps domains
• Be aware of best practices used in the Alphabet stack of ML technologies (e.g. TF, JAX, Flax, Beam etc)

Other

• B.S. in Computer Science, Math, or equivalent real-world experience
• 7+ years building and maintaining high-scale distributed or ML inference systems
• Previous experience deploying and supporting machine learning models for computer vision, natural language processing, or recommendation systems (preferred)
• Eligibility to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements