Job description

About the role: We are seeking a Senior AI Kernel Engineer to lead the design and optimization of high-performance kernels for large-scale AI inference on GPUs and emerging custom accelerators. In this role, you will own performance-critical paths, drive architectural decisions, and turn complex AI workloads into highly optimized implementations that run efficiently at scale. You will work at the intersection of hardware, compilers, and AI systems, collaborating closely with compiler, runtime, model, and infrastructure teams to deliver production-quality inference performance. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office. What you will do: • Design, implement, and optimize performance-critical kernels for AI inference workloads (e.g., GEMM, attention, communication, fusion). • Lead kernel-level optimization efforts across single-GPU, multi-GPU, and heterogeneous hardware environments. • Make informed trade-offs between latency, throughput, memory footprint, and numerical precision. • Drive adoption of new hardware features (e.g., Tensor Cores, asynchronous execution, advanced memory spaces). • Analyze performance using profilers, hardware counters, and microbenchmarks; translate insights into concrete improvements. • Work closely with compiler and runtime teams to influence code generation, scheduling, and kernel fusion strategies. • Review and mentor other engineers on kernel design, performance tuning, and best practices. • Contribute to technical roadmaps and long-term performance strategy for AI inference. What you bring to the table: • 5+ years of experience in performance-critical systems or kernel development (or equivalent depth of expertise). • Strong proficiency in C/C++ and low-level programming. • Extensive hands-on experience with GPU kernel programming (CUDA, HIP, or equivalent). • Deep understanding of GPU architecture , including memory hierarchies, synchronization, and execution models. • Proven track record of delivering measurable performance improvements in production systems. • Strong problem-solving skills and ability to work independently on complex, ambiguous performance challenges. Helpful, but not required: • Experience with PTX, assembly-level tuning, or code generation frameworks (e.g., Triton). • Experience optimizing distributed or multi-GPU inference pipelines. • Familiarity with custom AI accelerators or domain-specific hardware. • Understanding of modern AI models (e.g., transformers, LLMs, diffusion) from a systems and performance perspective. • Contributions to open-source kernel libraries, compilers, or performance tools. • Experience collaborating directly with hardware or compiler teams. What Modular brings to the table: • Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders. • World-class Benefits. In order to attract the best, we need to offer the best. Your benefits package may include comprehensive healthcare coverage, retirement and savings programs, employee stock purchase opportunities, paid time off, wellbeing resources, family support programs, and learning and development opportunities. Please note that specific benefit packages may vary based on your location, you can read more about benefits offered by Qualcomm here . • Competitive Compensation. We offer very strong compensation packages, including RSU grants. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. • Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is $180,000.00 - $324,000.00 USD . The estimated base salary range for this role to be performed in Canada, regardless of the province, is $172,400.00 - $310,400.00 CAD . The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have upcoming openings that are lower/higher level than the ones advertised.

Requirements

Must-haves

You will work at the intersection of hardware, compilers, and AI systems, collaborating closely with compiler, runtime, model, and infrastructure teams to deliver production-quality inference performance.
LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office.
Design, implement, and optimize performance-critical kernels for AI inference workloads (e.g., GEMM, attention, communication, fusion).
Lead kernel-level optimization efforts across single-GPU, multi-GPU, and heterogeneous hardware environments.
Make informed trade-offs between latency, throughput, memory footprint, and numerical precision.
Drive adoption of new hardware features (e.g., Tensor Cores, asynchronous execution, advanced memory spaces).
Analyze performance using profilers, hardware counters, and microbenchmarks; translate insights into concrete improvements.
Work closely with compiler and runtime teams to influence code generation, scheduling, and kernel fusion strategies.
Review and mentor other engineers on kernel design, performance tuning, and best practices.
Contribute to technical roadmaps and long-term performance strategy for AI inference.
5+ years of experience in performance-critical systems or kernel development (or equivalent depth of expertise).
Strong proficiency in C/C++ and low-level programming.
Extensive hands-on experience with GPU kernel programming (CUDA, HIP, or equivalent).
Deep understanding of GPU architecture , including memory hierarchies, synchronization, and execution models.
Proven track record of delivering measurable performance improvements in production systems.
Strong problem-solving skills and ability to work independently on complex, ambiguous performance challenges.
Experience with PTX, assembly-level tuning, or code generation frameworks (e.g., Triton).
Experience optimizing distributed or multi-GPU inference pipelines.
Familiarity with custom AI accelerators or domain-specific hardware.
Understanding of modern AI models (e.g., transformers, LLMs, diffusion) from a systems and performance perspective.
Contributions to open-source kernel libraries, compilers, or performance tools.
Experience collaborating directly with hardware or compiler teams.
Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.
Competitive Compensation. We offer very strong compensation packages, including RSU grants. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiagile

Platform: gem
Effort: medium

Benefits

Benefits detected in the listing.

Paid Time Off