WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. 

AMD together we advance_

THE ROLE: 

AMD is looking for a skilled and experienced engineer to join a core team of incredibly talented industry specialists working on developing a cutting-edge machine learning model compiler targeting AMD AIE in Ryzen AI PC and embedded FPGA devices. The compiler needs to take a model written in ONNX or PyTorch and produce optimized control and executable code for AIE VLIW processor array. Additionally, the compiler needs to handle partitioning between x86/embedded processor/FPGA fabric and AIE and generate code to interface with AMD AIE specific runtime and driver.

THE PERSON: 

The ideal candidate should be passionate about software system architecture and engineering. The candidate should possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.  

KEY RESPONSIBILITIES: 

• Define system architecture that provides easy-to-use interface for end users and seemless intergration with AMD runtime and AIE
• Integrate compiler and compiled model with ML Frameworks (such as ONNX and PyTorch)
• Implement model partitioning in ML Frameworks and/or MLIR
• Implement runtime to distribute work to and collect results from x86 cores and the array of AIE cores
• Learn latest industry trends and bring new ideas to the team
• Design and develop new groundbreaking AMD technologies
• Debugging/fix existing issues and research alternative, more efficient ways to accomplish the same work
• Mentor and provide guidance to others
• Develop technical relationships with peers and partners

PREFERRED EXPERIENCE: 

• Strong system architecture exeprience on end to end AI accleration solution
• Strong object-oriented programming background, C/C++ and Python
• ML Compiler and Runtime technologies: 
• Compiler building skills
• Code generation for a ML hardware accelerator
• Machine Learning concepts and model development experience
• Understanding of ONNX, PyTorch, etc.
• Ability to write high quality code with a keen attention to detail
• Experience with modern concurrent programming and threading APIs
• Experience with software development processes and tools such as debuggers, source code control systems (GitHub) and profilers is a plus
• Effective communication and problem-solving skills
• Motivating leader with good interpersonal skills

ACADEMIC CREDENTIALS: 

• Bachelor’s, Master's or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent

Location:

San Jose, Ca

#LI-JT1

At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

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.

At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

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.

THE ROLE: 

AMD is looking for a skilled and experienced engineer to join a core team of incredibly talented industry specialists working on developing a cutting-edge machine learning model compiler targeting AMD AIE in Ryzen AI PC and embedded FPGA devices. The compiler needs to take a model written in ONNX or PyTorch and produce optimized control and executable code for AIE VLIW processor array. Additionally, the compiler needs to handle partitioning between x86/embedded processor/FPGA fabric and AIE and generate code to interface with AMD AIE specific runtime and driver.

THE PERSON: 

The ideal candidate should be passionate about software system architecture and engineering. The candidate should possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.  

KEY RESPONSIBILITIES: 

• Define system architecture that provides easy-to-use interface for end users and seemless intergration with AMD runtime and AIE
• Integrate compiler and compiled model with ML Frameworks (such as ONNX and PyTorch)
• Implement model partitioning in ML Frameworks and/or MLIR
• Implement runtime to distribute work to and collect results from x86 cores and the array of AIE cores
• Learn latest industry trends and bring new ideas to the team
• Design and develop new groundbreaking AMD technologies
• Debugging/fix existing issues and research alternative, more efficient ways to accomplish the same work
• Mentor and provide guidance to others
• Develop technical relationships with peers and partners

PREFERRED EXPERIENCE: 

• Strong system architecture exeprience on end to end AI accleration solution
• Strong object-oriented programming background, C/C++ and Python
• ML Compiler and Runtime technologies: 
• Compiler building skills
• Code generation for a ML hardware accelerator
• Machine Learning concepts and model development experience
• Understanding of ONNX, PyTorch, etc.
• Ability to write high quality code with a keen attention to detail
• Experience with modern concurrent programming and threading APIs
• Experience with software development processes and tools such as debuggers, source code control systems (GitHub) and profilers is a plus
• Effective communication and problem-solving skills
• Motivating leader with good interpersonal skills

ACADEMIC CREDENTIALS: 

• Bachelor’s, Master's or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent

Location:

San Jose, Ca

#LI-JT1