AI Performance Engineer (Life Sciences)
Core
Optimize machine learning models and agentic AI systems for drug discovery by profiling, analyzing bottlenecks, and mapping workloads to GPU architectures.
Role type
Senior IC AI Performance Engineer (Life Sciences)
Builds
Production-grade AI systems for therapeutic impact
Domain
Life Sciences / High-Performance Computing / Deep Learning
Deliverable
production ML models
Required skills
Deep learning optimization, GPU kernel development, Profiling and bottleneck analysis, C++ and Python, PyTorch, CUDA/ROCm/HIP/Triton, Transformer architectures, Distributed computing
Preferred skills
Life sciences foundation models (AlphaFold, ESM, etc.), Life sciences simulation (GROMACS, NAMD), Cloud platforms (AWS, GCP, Azure), Cluster orchestration (Kubernetes, Slurm)
Technologies
PyTorch, CUDA, ROCm, HIP, Triton, TensorRT, Inductor, GROMACS, NAMD, AlphaFold, ESM, AWS, GCP, Azure, Kubernetes, Slurm
Responsibilities
Optimize ML models through profiling and bottleneck analysis, Analyze emerging ML models for compute/memory requirements, Develop GPU kernels for tensor operations, Collaborate with life sciences experts to translate requirements into technical solutions, Deliver high-quality, maintainable code aligned with open-source best practices
Seniority
Senior, hands-on IC
