WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

SENIOR SYSTEMS DESIGN ENGINEER

We are seeking a Senior Systems Design Engineer to develop and optimize ML operator kernels and dataflow pipelines for AMD's NPU platform. You will own the full lifecycle of ML operators — from kernel implementation and performance analysis to ONNX Runtime integration and NPU hardware integration. You will work with the very latest hardware and software technology as part of a core team of industry specialists. You will have full-stack visibility — from operator kernel development to silicon validation — on AMD's NPU shipping in millions of PCs. There are opportunities to publish and patent your work.

THE PERSON:

The ideal candidate combines deep systems-level expertise with hands-on ML inference experience. You thrive at the hardware-software boundary, are comfortable profiling and optimizing low-level code, and can drive complex cross-functional debug efforts to resolution.

JOB DETAILS:

• Location: San Jose, CA, US
• Onsite/Hybrid: This role requires the candidate to work full time (40 hours a week), either in a hybrid or onsite work structure.

WHAT YOU WILL BE DOING:

• Design and optimize NPU ML operator kernels and dataflow libraries across multiple datatypes (Int8, FP8, FP16, BF16)
• Profile operator and end-to-end model latency; identify bottlenecks and drive performance improvements
• Integrate and validate ML models within the ONNX Runtime framework on NPU
• Debug and resolve issues across the NPU compiler stack — from kernel correctness to system-level model accuracy
• Develop tiling strategies and optimize DMA data movement for on-chip memory utilization
• Perform roofline analysis and build performance models to guide kernel optimization
• Collaborate with silicon teams on hardware-software co-design for next-generation NPU

WHO WE ARE LOOKING FOR:

• Programming Languages: Strong proficiency in C/C++ and Python; experience with multithreading and concurrency
• ML Knowledge: Familiarity with ML operators (GeMM, Conv, Softmax, Attention) and inference frameworks (Py Torch, ONNX Runtime)
• System Knowledge: Understanding of computer architecture, memory hierarchies, cache behavior, and low-level hardware APIs
• Tools & Platforms: Proficiency with Git, debuggers, and profilers; experience
  with Linux development environments
• Preferred: Exposure to MLIR/LLVM compiler infrastructure
• Experience with NPU/GPU/accelerator kernel development or SDK integration
• Familiarity with quantization techniques (INT8, FP8) and accuracy debugging
• Experience with spatial architectures, systolic arrays, or dataflow accelerators
• Track record of publications or patents in ML systems, compilers, or computer architecture

KEY RESPONSIBILITIES:

• Drive technical innovation in NPU kernel and dataflow development, including tooling, benchmarks, and methodology improvements
• Debug and root-cause issues spanning silicon bring-up, validation, and production phases of SOC programs
• Coordinate cross-functionally with compiler, runtime, and hardware teams to ensure features are validated and performance targets are met on schedule
• Contribute to hardware/software co-design by engaging in modeling frameworks and architectural trade-off analysis

ACADEMIC CREDENTIALS:

• Masters or PhD degree in electrical or computer engineering

EXPERIENCE:

• 3+ years of relevant industry experience with Masters or PhD degree.

This role is not eligible for visa sponsorship.

#HYBRID

*Benefits offered are described: *AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.

SENIOR SYSTEMS DESIGN ENGINEER

We are seeking a Senior Systems Design Engineer to develop and optimize ML operator kernels and dataflow pipelines for AMD's NPU platform. You will own the full lifecycle of ML operators — from kernel implementation and performance analysis to ONNX Runtime integration and NPU hardware integration. You will work with the very latest hardware and software technology as part of a core team of industry specialists. You will have full-stack visibility — from operator kernel development to silicon validation — on AMD's NPU shipping in millions of PCs. There are opportunities to publish and patent your work.

THE PERSON:

The ideal candidate combines deep systems-level expertise with hands-on ML inference experience. You thrive at the hardware-software boundary, are comfortable profiling and optimizing low-level code, and can drive complex cross-functional debug efforts to resolution.

JOB DETAILS:

• Location: San Jose, CA, US
• Onsite/Hybrid: This role requires the candidate to work full time (40 hours a week), either in a hybrid or onsite work structure.

WHAT YOU WILL BE DOING:

• Design and optimize NPU ML operator kernels and dataflow libraries across multiple datatypes (Int8, FP8, FP16, BF16)
• Profile operator and end-to-end model latency; identify bottlenecks and drive performance improvements
• Integrate and validate ML models within the ONNX Runtime framework on NPU
• Debug and resolve issues across the NPU compiler stack — from kernel correctness to system-level model accuracy
• Develop tiling strategies and optimize DMA data movement for on-chip memory utilization
• Perform roofline analysis and build performance models to guide kernel optimization
• Collaborate with silicon teams on hardware-software co-design for next-generation NPU

WHO WE ARE LOOKING FOR:

• Programming Languages: Strong proficiency in C/C++ and Python; experience with multithreading and concurrency
• ML Knowledge: Familiarity with ML operators (GeMM, Conv, Softmax, Attention) and inference frameworks (Py Torch, ONNX Runtime)
• System Knowledge: Understanding of computer architecture, memory hierarchies, cache behavior, and low-level hardware APIs
• Tools & Platforms: Proficiency with Git, debuggers, and profilers; experience
  with Linux development environments
• Preferred: Exposure to MLIR/LLVM compiler infrastructure
• Experience with NPU/GPU/accelerator kernel development or SDK integration
• Familiarity with quantization techniques (INT8, FP8) and accuracy debugging
• Experience with spatial architectures, systolic arrays, or dataflow accelerators
• Track record of publications or patents in ML systems, compilers, or computer architecture

KEY RESPONSIBILITIES:

• Drive technical innovation in NPU kernel and dataflow development, including tooling, benchmarks, and methodology improvements
• Debug and root-cause issues spanning silicon bring-up, validation, and production phases of SOC programs
• Coordinate cross-functionally with compiler, runtime, and hardware teams to ensure features are validated and performance targets are met on schedule
• Contribute to hardware/software co-design by engaging in modeling frameworks and architectural trade-off analysis

ACADEMIC CREDENTIALS:

• Masters or PhD degree in electrical or computer engineering

EXPERIENCE:

• 3+ years of relevant industry experience with Masters or PhD degree.

This role is not eligible for visa sponsorship.

#HYBRID

*Benefits offered are described: *AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.