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Waymo is seeking an experienced Staff Machine Learning Infrastructure Engineer to lead the development of AI/ML systems for large-scale foundation models tailored for autonomous driving simulations. The role is based in London and will involve working collaboratively with teams in both London and Oxford. This position requires deep expertise in machine learning infrastructure, distributed computations, and optimization techniques for large-scale models.
• You have 8+ years of professional software engineering experience, with at least 5 years focused on machine learning infrastructure. • You have deep expertise in optimizing and scaling large machine learning models, particularly using tools such as DeepSpeed, PyTorch, TensorFlow, or Ray. • You are experienced in distributed training strategies, including gradient sharding and system optimizations for ML accelerators. • You understand and have worked on autoregressive transformer models. • You excel at leading technical discussions across cross-functional engineering teams and can translate complex concepts into actionable strategy. • You are familiar with autonomous driving, large-scale simulations, and ML accelerators (preferred but not required).
• Lead the design and scaling of large distributed systems for the full ML lifecycle, including data generation, training, and evaluation. • Collaborate with the core Waymo Realism Modeling team to integrate large foundation models into simulations for increased realism. • Provide deep technical leadership on ML architectures, focusing on high-fidelity autonomous vehicle models. • Optimize and enhance infrastructure to support processing at the scale required for autonomous driving training and simulation. • Define system-level requirements ensuring alignment between business objectives and technical solutions. • Mentor junior engineers, fostering a culture of collaboration and technical excellence.
• Competitive base salary with potential for discretionary annual bonuses. • Equity incentive plan for long-term compensation. • Comprehensive health and wellness benefits, including medical, dental, and vision coverage. • Opportunity to work with cutting-edge autonomous vehicle technology in a world-class research environment. • Flexible working environment and collaboration with international teams. • Professional development opportunities, including mentorship and leadership growth programs.
• Waymo is committed to fostering an inclusive work environment where employees of all backgrounds are valued. • The company actively promotes equitable hiring practices and encourages diversity in technical and leadership positions. • Employee resource groups and mentoring programs are available to support underrepresented communities in tech. • Waymo believes in fair compensation and internal career growth opportunities to reduce systemic inequities in the industry. • The company supports social initiatives aimed at making autonomous vehicle technology more accessible to diverse communities.
• Waymo is placing a strong emphasis on diversity and inclusion in tech leadership roles, ensuring fair hiring practices. • The company provides structured mentorship and career development programs to uplift underrepresented engineers. • Employee benefits and equity programs are designed to create long-term opportunities and financial security for a diverse workforce. • Waymo is actively working toward making autonomous vehicle technology more accessible beyond traditional user demographics.
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