GPU ML Modeling / MLOps Engineer Job Listing at AMD in Warsaw, Masovian Voivodeship (Job ID 71629-en-us)

Description

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_

GPU ML Modeling / MLOps Engineer

THE ROLE:

AMD is looking for a strategic ML Engineer who is passionate about Machine Learning, Visual Computing, and Gaming.

KEY SKILLS:

Computer Vision; Image Processing (ML), Graphic Data Analytics

THE PERSON:

The ideal candidate is a highly skilled software or machine learning engineer, with expertise in training models, especially for computer vision or graphics tasks. You are interested in Machine Learning, and you are excited to have a real impact on the future of gaming by unlocking the next generation of software technologies for graphics. You are team-driven and motivated to do things that others might find too difficult.

KEY RESPONSIBILITIES:

• Train and maintain ML models for CV / CG.
• Improve ML workflows using tools such as data versioning, MLOps platforms, or automation pipelines.
• Curate datasets to train and evaluate models.
• Analyze model behavior to make sure we deliver the best visual quality for gamers.
• Collaborate with cross-functional teams incl. researchers, engineers, and domain experts to understand requirements, develop prototypes, and deploy production-ready ML solutions.
• Document code, methodologies, and findings comprehensively, ensuring reproducibility and knowledge sharing within the team and across the organization.
• Mentor junior team members, providing guidance on machine learning concepts, programming techniques, and software development practices to foster skill development and team growth.

PREFERRED EXPERIENCE:

• Minimum of 2 years in a full-time (post grad) Data Scientist / Analyst position.
• Proficiency in Python for rapid prototyping and testing, incl. understanding of general software development principles, version control systems, and CI pipelines.
• Experience with ML libraries such as PyTorch, ONNX, and similar.
• Familiarity with GPU Compute APIs such as Direct3D/HLSL, CUDA, or ROCm/HIP.
• Ability to write high-quality, maintainable code with meticulous attention to detail, ensuring robustness and optimal performance.
• Proficiency in English, with excellent written and verbal communication skills, to collaborate effectively. Ability to articulate complex technical concepts to both technical and non-technical stakeholders.

The following points are optional but highly desired:

• Passion for computer games and game graphics.
• Familiarity with algorithms behind 3D graphics incl. ray tracing techniques.
• GCN / RDNA graphics or game console architecture experience.
• Game engine or game rendering framework experience.

ACADEMIC CREDENTIALS: 

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

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.