AI Performance Engineer (life sciences)

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_

Main Responsibilities

• AI Performance Engineers focus on optimizing machine learning models, profiling, bottleneck analysis, and optimal mapping to GPU.
• As an AI Performance Engineer, you will analyze and explore recent ML models, understand their compute and memory requirements, and optimize them on various compute hardware for both inference and training.
• In addition, you will profile and analyze various workloads on current hardware and come up with new ways to improve their performance.
  
  
  

Collaboration With Others 

• The position is part of the life sciences workstream at AMD Silo AI’s R&D and Models unit. 
• Collaborate with life sciences AI developers and domain experts to communicate and understand the requirements. 
• Work with multiple teams located in Finland locally and internationally in the organization.
• Communicate with clients to explain performance bottlenecks and resolutions
  
  
  

Main Goals For First 6 Months

• Benchmark, analyze, and optimize performance of key machine learning applications, on single and multi-GPU systems
• Design, implement, and test GPU kernels and algorithms for tensor operations like matrix multiplication and convolutions used in a variety of high-performance machine learning libraries and frameworks
• Deliver high-quality code and documentation following best practices for open-source software development
  
  
  

Ideal Candidate Profile

• The ideal candidate will have strong experience with
• software optimization,
• GPU programing,
• hardware architecture and
• life sciences software development.
• Passionate of getting the best performance out of various hardware’s under different tradeoffs.
• If you are passionate about performance optimization, getting the best out of the HW, and shaping the future performance, then this role is for you.
  
  
  

Required Skills And Qualifications 

• Understanding of GPU architectures and low-level optimization techniques, memory hierarchy, instruction scheduling, and performance tradeoffs
• GPU software development using HIP, CUDA, or OpenCL
• In-depth knowledge of best-practices in software development, including testing, profiling, debugging, documentation, version control, issue tracking, and planning
• Experience with C++ and Python programming
• Experience in PyTorch, MIOpen
• Experience in high-performance computing (HPC)
• Strong written and spoken English language skills (our company language)
• Experience with singularity, or docker, Slurm or Kubernetes components & subsystems
• BSc, MSc, PhD or equivalent experience in Computational Chemistry, Bio Physics, Bioinformatics or a related field
  
  
  

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 together we advance_