Staff Machine Learning Accelerator Architect
Job Title: Staff Machine Learning Accelerator Architect
Location: On-Site (Flexible)
Company: Waymo
Industry: AI, Machine Learning, Hardware Engineering
About the Role:
Are you ready to make an impact at the intersection of cutting-edge hardware and machine learning? As a Staff ML Accelerator Architect, you’ll play a pivotal role in designing and optimizing the next generation of hardware platforms that power machine learning at scale. You’ll work on some of the most advanced architectures, working hand-in-hand with both hardware and software teams to accelerate AI applications across industries.
In this role, you’ll be a thought leader in ML hardware, architecting specialized accelerators that push the boundaries of performance and efficiency. You'll collaborate with a world-class team of engineers to create the future of AI and machine learning infrastructure, driving innovation that powers everything from cloud computing to edge devices.
This is a high-impact position where your expertise will be critical in shaping the evolution of machine learning workloads and ensuring that hardware can meet the needs of the rapidly advancing field of AI.
What You’ll Do:
Architect ML Accelerators: Lead the design and architecture of custom accelerators for machine learning workloads, focusing on performance, scalability, and efficiency.
Collaborate Across Teams: Work closely with machine learning engineers, software developers, and hardware designers to optimize end-to-end ML system performance and enable the seamless integration of ML workloads into hardware.
Design Innovative Solutions: Drive innovations in hardware architecture that specifically enhance AI performance, enabling real-time, large-scale machine learning and deep learning models.
Optimize for Performance: Continuously evaluate and optimize the performance of machine learning systems, ensuring that accelerators are tailored for specific ML tasks and data types (e.g., vision, NLP, reinforcement learning).
Research & Innovation: Stay on the cutting edge of hardware and machine learning trends to continuously incorporate emerging technologies and methodologies into your designs.
Scale ML Infrastructure: Lead efforts to ensure that ML accelerators scale efficiently from the data center to the edge, optimizing both cost and performance.
Mentorship: Mentor junior engineers, fostering a culture of excellence and innovation in hardware and software development.
What We’re Looking For:
10+ years of experience in hardware architecture, with a focus on machine learning accelerators or similar domains (e.g., GPUs, TPUs, custom ASICs).
Expertise in machine learning models and workloads, particularly in training and inference, and understanding how hardware accelerators can optimize them.
Deep experience with hardware design (FPGA, ASIC) and hardware/software co-design, including experience with tools like Verilog, VHDL, or high-level synthesis tools.
Familiarity with ML frameworks (TensorFlow, PyTorch, JAX) and how they interface with hardware.
Strong programming skills in C/C++ and familiarity with low-level hardware optimization techniques.
Experience with system-level architecture and understanding of how to balance performance, power, and area (PPA) trade-offs in accelerator designs.
Ability to analyze and optimize machine learning models, making them more efficient and adaptable to specialized hardware.
Strong communication and leadership skills to drive projects and work cross-functionally with teams across the organization.
Bonus Points:
Contributions to open-source hardware projects or publications in AI hardware and accelerator design.
Experience with edge computing and designing accelerators for resource-constrained environments.
Familiarity with cloud-based hardware acceleration and optimizing accelerators for distributed environments.
Advanced degree (Ph.D. or M.S.) in Electrical Engineering, Computer Engineering, Computer Science, or a related field with a focus on hardware design or AI.
Why Waymo?
Cutting-edge Technology: Work on the frontier of AI and hardware, building the tools and infrastructure that power next-gen machine learning applications.
Impactful Work: Join a team where your work directly impacts large-scale AI systems, from data centers to edge devices.
Collaborative Culture: Thrive in a dynamic environment with talented engineers, researchers, and thought leaders across hardware, software, and AI.
Flexible Environment: Enjoy flexible working arrangements, including remote or hybrid options, to fit your lifestyle.
Competitive Benefits: Comprehensive compensation package including salary, performance-based bonuses, equity, and generous perks.
Growth & Development: With opportunities for mentorship, career progression, and continuous learning, you’ll be set up to grow into a true leader in the field.
Key Skills: