Principal Software Engineer, ML System Architect

The Waymo Systems Intelligence and Machine Learning (SIML) team is seeking a Principal Software Engineer to lead the development and integration of large-scale foundation models, such as those from Google DeepMind like Gemini, into Waymo’s autonomous driving ecosystem. This role will focus on architecting and building a unified AI platform that leverages these models to enhance the Waymo Driver.

Architect ML Systems

• Define and drive the technical roadmap for the platform, encompassing codebase unification, data pipelines, model architecture, training recipes, and evaluation frameworks.
• Lead the unification of existing forked locations of foundation model component codebases into a production-hardened, shared repository.
• Establish and enforce rigorous coding standards, testing practices, and API designs to ensure long-term codebase health and developer velocity.
• Serve as the primary technical interface between Waymo's offboard model development and Google Deepmind's core model and framework teams.
• Define clear APIs and integration patterns, ensuring Waymo can seamlessly leverage and contribute to Google Deepmind's advancements while maintaining stability and control.
• Drive the consolidation of tokenization/de-tokenization strategies, data formats, input pipelines, and evaluation methodologies across all offboard Foundation Model use cases.
• Architect for efficient large-scale distributed training (large scale) and establish a common, efficient distillation setup to transfer knowledge from large teacher models to onboard student models.

Technical Leadership & Influence

• Provide technical mentorship, guidance, and direction to engineers across multiple teams within SIML and AI Foundations.
• Drive alignment on technical decisions with senior stakeholders across Waymo and Google Deepmind.
• Drive efficiency in model development, training, and resource utilization, aiming for high ML productivity.

Experience

• Master's degree or PhD in Computer Science or a related field.
• 12+ years of experience in software engineering, with at least 8+ years focused on large-scale machine learning systems, deep learning frameworks, and AI infrastructure.
• Deep expertise in Python, C++, and ML frameworks like JAX and TensorFlow.
• Extensive experience with large-scale distributed training on TPUs/GPUs and associated challenges.
• Understanding of data pipelines, storage systems, and tokenization techniques.
• Experience working effectively with research and product teams, and influencing across organizational boundaries.
• Technical leadership skills, with the ability to drive strategy, influence across teams, and mentor other engineers.
• Communication skills, with the ability to articulate complex technical vision and drive alignment, capable of conveying complex technical ideas clearly.

We prefer candidates with experience with multimodal and generative models, experience in autonomous vehicle systems or robotics, contributions to open-source ML frameworks or widely used internal tools, and experience with simulation systems.