Application Software Optimization Engineer, HPC/AI Outreach & Enablement

AMD's Center of Excellence (CoE) is seeking an Application Software Optimization Engineer focused on HPC and AI training and technical enablement. This position will have primary responsibility for developing, coordinating, and delivering the LUMI CoE training program, while expanding those programs and materials to support customers, users, and technical communities across EMEA.

The engineer will work closely with LUMI, LUMI users, Bull, AMD technical teams, and other regional partners to identify training requirements and translate them into repeatable technical training and onboarding programs. This includes hands-on workshops, technical tutorials, application enablement sessions, and training materials covering AMD GPU architectures, ROCm, HPC application development, AI workloads, profiling, debugging, optimization, and scaling.

The role will serve as a technical training lead for the LUMI CoE, helping establish a scalable training model that can be reused across LUMI and other strategic AMD HPC and AI engagements throughout EMEA.

The position should be based in, or willing to relocate to, Sweden or EMEA, with the ability to travel to LUMI and other customer and partner sites as required.

THE PERSON

A computational scientist, engineer, or technical educator with a strong background in HPC and/or AI and a demonstrated ability to translate complex technical concepts into effective hands-on training.

The ideal candidate combines technical depth with strong communication and teaching skills. They should be comfortable working directly with scientists, application developers, user-support teams, system administrators, and new users with different levels of GPU experience.

The candidate should have experience with GPU programming and performance optimization and be capable of developing practical examples, exercises, tutorials, and workshops that help users successfully transition applications and AI workloads to AMD platforms.

They must be self-motivated, collaborative, comfortable presenting to groups, and capable of coordinating training activities across geographically distributed teams.

KEY RESPONSIBILITIES

• Own and coordinate the LUMI CoE technical training program, working with LUMI, Bull, AMD, application teams, user-support organizations, and other stakeholders to identify training needs and establish priorities.
• Develop and maintain a LUMI training roadmap and curriculum covering onboarding, AMD GPU architecture, ROCm, application porting, profiling, debugging, optimization, scaling, and AI/HPC workflows.
• Develop and deliver hands-on workshops, tutorials, labs, examples, and technical training materials for LUMI users and support personnel.
• Establish repeatable training content and delivery models that can be extended from LUMI to strategic HPC and AI customers throughout EMEA.
• Coordinate AMD subject-matter experts and CoE engineers contributing specialized material to training sessions.
• Work directly with users to understand common onboarding, programming, application-porting, and performance challenges and incorporate those lessons into future training.
• Develop training paths for different audiences, including new users, application developers, HPC experts, user-support teams, and AI practitioners.
• Support customer workshops, hackathons, boot camps, conferences, and other technical outreach activities.
• Maintain and continuously improve training materials as AMD hardware, ROCm software, libraries, tools, and recommended programming practices evolve.
• Develop, port, and optimize representative HPC and AI applications and examples for use in training and customer enablement.
• Work collaboratively with other CoE engineers to resolve technical issues identified during training and user onboarding.
• Represent AMD to customers, partners, academic institutions, and other third parties.
• Serve as an advocate for user and training requirements when working with AMD engineering and product teams.
• Measure training effectiveness and use participant feedback, common technical issues, and user adoption patterns to improve the program.

ACADEMIC CREDENTIALS AND PREFERRED EXPERIENCE

• PhD in Computer Science, Computational Physics, Engineering, or a related discipline, or equivalent industry/research experience.
• At least 5 years of relevant HPC and/or AI experience in research, academia, or industry.
• Experience developing or delivering technical training, workshops, tutorials, university instruction, hackathons, or developer-enablement programs is highly desirable.
• Experience with GPU programming and/or performance engineering using technologies such as HIP, CUDA, OpenMP, MPI, C/C++, Python, or Fortran.
• Familiarity with HPC and GPU profiling, debugging, libraries, compilers, and performance-analysis tools.
• Experience with AI frameworks such as PyTorch or other modern AI/ML frameworks is desirable.
• Strong technical presentation, written communication, and interpersonal skills.
• Ability to work effectively with geographically distributed teams and diverse technical audiences.
• Ability and willingness to travel throughout EMEA for customer training and technical outreach activities.