Staff Engineer, Compiler

Samsung Semiconductor • San Jose, CA

1d • Onsite

About The Position

The AGI (Artificial General Intelligence) Computing Lab tackles system-level challenges created by the growing demands of future AI/ML workloads. The team designs and develops scalable platforms to meet the computational and memory needs of these workloads while minimizing energy consumption and maximizing performance. It works closely with hardware and software engineers to address workload-specific challenges, explore new computing abstractions, and research emerging trends in memory, computing, interconnect, and AI/ML.

The Staff Engineer, Compiler will lead the architecture, design, and implementation of ML compilers for high-performance deep learning applications targeting next-generation AGI hardware platforms. The role develops staged lowering infrastructure and novel optimization algorithms, and partners with hardware teams to co-design instructions, memory architectures, and computing abstractions. The engineer also aligns cross-functional teams, provides technical leadership through reviews and mentoring, troubleshoots complex compiler and performance issues, and develops documentation and best practices.

The position requires daily onsite presence at Samsung Semiconductor’s San Jose, California office/U.S. headquarters, in alignment with its Flexible Work policy.

Requirements

• Bachelor’s degree with 10+ years, Master’s degree with 8+ years, or Ph.D. with 5+ years of industry experience.
• Strong background in compiler design and optimization techniques.
• Experience developing and optimizing software for high-performance computing systems.
• Familiarity with PyTorch, TensorFlow, or JAX.
• Familiarity with hardware architectures such as CPUs, GPUs, TPUs, and NPUs.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills.
• Ability to work independently and as part of a team.
• Inclusive approach, adapting communication and work style to different situations and diverse global norms.
• Curiosity and resilience, with a willingness to use data to build understanding.
• Collaborative approach, including building relationships, offering support, and welcoming others’ approaches.
• Innovative and creative approach, with the ability to explore new ideas and adapt to change.
• Daily onsite presence at the San Jose, California office/U.S. headquarters.

Nice To Haves

• Experience with LLVM or MLIR.

Responsibilities

• Lead the architecture, design, and implementation of ML compilers for high-performance deep learning applications targeting next-generation AGI hardware platforms.
• Design and evolve staged lowering infrastructure to adapt to changing workload requirements and new hardware features.
• Invent and implement optimization algorithms for data locality, memory scheduling, kernel fusion, and code generation to reduce energy consumption and maximize performance on AI accelerator systems.
• Bridge compiler and hardware teams by co-designing instructions, memory architectures, and computing abstractions, and ensuring the compiler makes full use of them.
• Influence and align hardware, runtime, ML framework, and research teams to define and deliver ML compiler features and improvements.
• Raise engineering standards through design and code reviews, mentoring, and technical standards for compiler development.
• Troubleshoot and debug complex compiler and performance issues, guiding the team toward root causes and durable solutions.
• Develop compiler documentation, user guides, and best practices.

Benefits

• Medical, dental, and vision benefits.
• 401(k).
• Incentive opportunities based on individual and company performance.
• Charitable giving match and opportunities to participate in community activities.
• 4+ weeks of paid time off per year, plus holidays and sick leave.
• Fertility care or adoption stipend, caregiver support, and medical travel support.
• On-demand emotional wellness apps and free confidential therapy sessions.
• Onsite café and gym, plus virtual fitness classes.
• Flexible work environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior