Technical Lead Manager (Prediction, ML Evaluation)

Join Waymo's Predictive Planning team as a Staff Technical Lead Manager. In this role, you will define the strategic vision for our ML Evaluation team, collaborate cross-functionally with ML engineers and data scientists, and manage and mentor a focused team of engineers. You will also drive best practices and stay at the forefront of emerging technologies in ML evaluation methodologies. Enjoy a comprehensive benefits package, including medical, dental, and vision insurance, competitive compensation, and a hybrid work model.

• Definir la visión estratégica para las plataformas de evaluación, escalando la infraestructura crítica y las métricas requeridas.
• Colaborar de manera transversal con ingenieros de ML, científicos de datos y equipos de infraestructura para identificar y definir señales críticas sobre el rendimiento del modelo.
• Gestionar y mentorizar a un equipo enfocado de ingenieros, alineando su crecimiento profesional y aspiraciones con las necesidades organizativas críticas.
• Familiarity with large-scale ML deployment and orchestration tools (e.g., TF Serving, TorchServe, Kubeflow, SageMaker Pipelines, or Vertex AI Pipelines)
• M.S. in Computer Science, Mathematics, or equivalent industry experience in Robotics or large-scale ML systems with critical evaluation needs
• Strong coding and testing proficiency, specifically in Python and C++
• Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow
• 5+ years of experience building and maintaining large-scale distributed infrastructure, ML inference systems, or evaluation platforms, including 3+ years of engineering management experience
• Strong foundational knowledge of model evaluation and core data science principles (e.g., confidence intervals, outlier identification, curve fitting, and causality analysis)
• Experience developing and maintaining evaluation pipelines for ML models
• Experience deploying and supporting machine learning models for computer vision, natural language processing, robotics/motion planning, or recommendation systems
• Experience supporting a small team of MLEs developing high-capacity, production-grade models and components
• Strong understanding of metrics computation and regression detection at scale