Kernel Engineer for AI Inference Performance

Acceler8 Talent; San Francisco (CA); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Acceler8 Talent is seeking a Member of Technical Staff for Kernels & GPU Performance in San Francisco, on-site. The role focuses on building and optimizing low-level execution primitives to translate accelerator capability into production AI performance, spanning multiple accelerator architectures.

You will work near hardware across kernel implementation, memory access, profiling, and validation, partnering with compiler, ML systems, runtime, and distributed-systems engineers to improve latency,

Qualifications

• Bachelor's degree in a relevant technical discipline or equivalent practical experience.
• Strong software-engineering fundamentals and experience near hardware.
• Ability to reason about memory hierarchies, compute utilization, scheduling and tradeoffs.
• Experience profiling, debugging, and optimizing for latency and throughput.

Responsibilities

• Build and optimize kernels for production AI workloads.
• Improve latency, throughput, and hardware utilization across accelerators.
• Develop execution strategies across multiple accelerator architectures.
• Analyze memory hierarchies and bottlenecks to optimize performance.
• Profile and validate performance across diverse hardware platforms.
• Collaborate with compiler, runtime, ML systems, and distributed-systems engineers.

Skills

Software engineering

Performance-critical systems

Low-level execution

Memory hierarchy

Profiling & debugging

Latency & throughput optimization

Education

Bachelor's degree in a technical field

Tools

CUDA

Triton

CUTLASS

GPU kernel development

Accelerator programming

Job description

Acceler8 Talent is seeking a Member of Technical Staff for Kernels & GPU Performance in San Francisco, on-site. The role focuses on building and optimizing low-level execution primitives to translate accelerator capability into production AI performance, spanning multiple accelerator architectures.

You will work near hardware across kernel implementation, memory access, profiling, and validation, partnering with compiler, ML systems, runtime, and distributed-systems engineers to improve latency,