| Location | Anywhere, CA |
Are you a visionary technical leader passionate about defining the future of AI infrastructure and squeezing every drop of performance out of advanced hardware accelerators at scale? We are seeking a Principal Architect to lead, shape, and execute our technical strategy for AI performance, optimization, and hardware-software co-design.
In this elite, highly visible role, you will define the architectural vision for both AI training and serving infrastructure, delivering massive industry-wide impact. You will spearhead our Center of Excellence (CoE), scaling our practice and guiding the technical roadmap across next-generation Tensor Processing Units (TPUs), Graphics Processing Unit (GPU) fleets, state-of-the-art ML models, and advanced compiler toolchains.
Your architectural decisions will directly enable cutting-edge AI research and large-scale production deployments across Google Cloud, major enterprise customers, and the broader open-source ecosystem. If you thrive on solving intractable performance bottlenecks and redefining what is physically and computationally possible in AI infrastructure, this is your platform.
Responsibilities
• Define and drive the multi-year technical roadmap for high-performance AI kernels, custom operations, and hardware-software co-design targeting TPU and GPU architectures
• Scale and mentor a world-class technical practice, establishing architectural governance, engineering standards, and best practices across the organization
• Act as the principal technical liaison partnering with ML researchers, core framework architects (JAX, PyTorch), and compiler engineering teams (XLA, MLIR) to eliminate systemic bottlenecks and shape future hardware/software requirements
• Architect foundational infrastructure—including enterprise-grade benchmarking suites, automated autotuning frameworks, regression analysis pipelines, and comprehensive documentation—empowering the global developer community
• Anticipate industry shifts by tracking advancements in hardware architectures, emerging model topologies, and compiler innovations to unlock step-changes in AI training and inference efficiency
Requirements
• Bachelors degree in Computer Science, Electrical Engineering, or equivalent practical experience (Masters or Ph.D. preferred)
• 15+ years of software engineering experience, with 8+ years focused on distributed systems, AI infrastructure, or high-performance computing (HPC) architecture
• 7+ years of experience designing and developing complex software systems in C++ or Python
• 5+ years of experience leading the architecture, design, and delivery of large-scale software products, frameworks, or developer ecosystems from inception to production
• Proven track record of architecting performance-critical systems at the kernel level, bridging hardware accelerators and high-level software frameworks
Nice to have
• Deep expertise in optimizing TPU/GPU execution, leveraging low-level kernel languages/abstractions such as Pallas, Mosaic, Triton, or CUDA
• Comprehensive knowledge of modern ML frameworks (JAX, PyTorch), attention mechanisms, Mixture of Experts (MoEs), model quantization, and low-precision arithmetic
• Advanced understanding of modern accelerator architectures, including heterogeneous compute, complex memory hierarchies, data movement optimization, and multi-node scale-out fabrics
• Deep familiarity with compiler principles, code generation, and modern toolchains such as MLIR, OpenXLA, and LLVM
• Demonstrated leadership in building and scaling developer infrastructure, widely adopted Open-Source Software (OSS) libraries, and extensible high-performance APIs
• Exceptional strategic communication and stakeholder management skills, with a history of influencing cross-functional engineering teams, researchers, and executive leadership
We offer/Benefits
• Medical, Dental and Vision Insurance (Subsidized)
• Health Savings Account
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Short-Term and Long-Term Disability (Company Provided)
• Life and AD&D Insurance (Company Provided)
• Employee Assistance Program
• Unlimited access to LinkedIn learning solutions
• Matched 401(k) Retirement Savings Plan
• Paid Time Off – the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)
• Paid Holidays - nine (9) total per year
• Legal Plan and Identity Theft Protection
• Accident Insurance
• Employee Discounts
• Pet Insurance
• Employee Stock Purchase Program
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program