AI Performance Engineer (Life Sciences)
Helsinki, FinlandFull-timePosted 1mo ago
About the role
Role focused on development and optimization of foundation models and agentic AI systems for drug discovery within a multidisciplinary Life Sciences R&D context at AMD.
Responsibilities
- Optimize machine learning models through profiling, bottleneck analysis, and efficient mapping of workloads to GPU architectures.
- Analyze emerging machine learning models, understand their compute and memory requirements, and optimize them for training and inference across a range of hardware platforms.
- Perform optimization at the kernel, framework, and hardware levels.
- Work hands-on with deep learning and transformer architectures, as well as physics-based simulation models.
- Profile and analyze workloads on current hardware, identify performance bottlenecks, and develop strategies to improve efficiency and scalability.
Qualifications
- A Master’s degree, PhD, or equivalent practical experience in Computer Science, Computer Engineering, Computational Science, Applied Mathematics, Cheminformatics, Bioinformatics, or a related field.
- Relevant experience developing and delivering machine learning, simulation, or high-performance computing solutions.
- Experience building machine learning and simulation applications and pipelines.
- A strong understanding of deep learning architectures, including transformers, diffusion models, and language models.
- Proficiency in Python and familiarity with C++ in production environments.
- Experience with PyTorch; familiarity with JAX would be beneficial.
- Software engineering skills across rapid prototyping, debugging, profiling, optimization, and the delivery of maintainable production code.
- Familiarity with AI-assisted development tools, such as Claude Code or Cursor.
- Experience with performance profiling tools such as rocprof, PyTorch Profiler, or Nsight.
- Experience with framework-level optimization, including compilation techniques and backends such as Inductor or TensorRT.
- Experience profiling and optimizing GPU workloads using ROCm and/or CUDA.
- GPU software development experience using technologies such as HIP, CUDA, or OpenCL.
- Experience developing GPU kernels with HIP, CUDA, or Triton.
- Experience working in high-performance computing environments.
- Effective written and verbal communication and presentation skills in English.
Skills
Required:Master’s degree / PhD or equivalentMachine learning and simulation developmentDeep learning architectures (transformers, diffusion models, language models)PythonPyTorchPerformance profiling tools (rocprof, PyTorch Profiler, Nsight)GPU optimization (HIP, CUDA, OpenCL)GPU kernel development (HIP, CUDA, Triton)High-performance computingCommunication skills
Nice to have:C++
Benefits
- Benefits offered are described: AMD benefits at a glance.
Last updated Oct 22, 2026. Interested? Apply on the company site.
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