Life Sciences AI Research Engineer

Advanced Micro Devices, Inc • Longmont, CO

4h

About The Position

AMD is seeking a hands-on research engineer to advance life sciences computing at the intersection of computational biology, AI, and high-performance computing. The role investigates emerging scientific workloads, develops and optimizes algorithms, and builds software that helps researchers address larger and more complex biological problems on AMD platforms. Relevant areas include genomics, biological foundation models, protein and molecular modeling, and computational drug discovery.

The engineer works with AMD researchers, software engineers, and external collaborators, taking projects from scientific problem definition through implementation and evaluation. Findings help identify opportunities for AMD in life sciences computing and inform future research and software investments. The role requires expertise in a computational life sciences domain, strong programming skills, and the ability to evaluate whether technical improvements benefit scientific workflows and communicate findings to both domain scientists and systems engineers.

Requirements

• Strong computational expertise in at least one life sciences area, such as computational genomics, bioinformatics, protein modeling, computational chemistry, or molecular simulation.
• Hands-on experience implementing scientific algorithms or developing machine learning models for biological applications.
• Strong Python programming skills and experience with C++ or another language used for high-performance scientific computing.
• Solid understanding of algorithms, data structures, numerical methods, and experimental evaluation.
• Experience profiling, debugging, and improving computational software.
• Ability to work independently on a defined technical problem and collaborate effectively across scientific and engineering disciplines.
• Clear written and verbal communication skills.

Nice To Haves

• Experience with biological foundation models, protein structure prediction or design, molecular generative models, or genomic sequence modeling.
• Experience with scientific AI architectures such as transformers, geometric deep learning, graph neural networks, or diffusion models.
• GPU programming and optimization using HIP, CUDA, Triton, or comparable technologies.
• Experience with deep learning frameworks such as PyTorch, including custom operators or distributed training and inference.
• Experience with parallel algorithms, multi-GPU computing, or large-scale scientific workflows.
• Familiarity with established life sciences software ecosystems and experience extending or contributing to open-source tools.
• Research contributions demonstrated through publications, software, patents, or deployed scientific applications.
• Master’s or PhD in Computational Biology, Bioinformatics, Computer Science, Applied Mathematics, Computational Chemistry, or a related discipline, or equivalent practical experience.

Responsibilities

• Investigate important and emerging life sciences workloads, including their scientific objectives, algorithms, computational requirements, and practical limitations.
• Develop, implement, and evaluate algorithms and AI methods for genomics, biomolecular modeling, or related applications.
• Profile and optimize scientific applications and AI workflows on AMD platforms, addressing computation, memory, data-processing, and communication bottlenecks.
• Explore algorithmic reformulations, parallelization strategies, numerical precision, and GPU acceleration while preserving scientific validity.
• Build reproducible benchmarks measuring end-to-end performance, scalability, resource use, and relevant scientific outcomes.
• Work with academic and industry collaborators to translate scientific needs into technical requirements and working implementations.
• Contribute reusable software, optimized operators, and improvements to relevant open-source projects.
• Translate experimental findings into recommendations for AMD research priorities, software capabilities, and hardware requirements.
• Communicate results through technical reports, demonstrations, publications, and invention disclosures, as appropriate.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level