Senior Machine Learning Engineer (Large Systems)
Core
Develop and optimize state-of-the-art AI models for specialized hardware across thousands of accelerators.
Role type
Senior Machine Learning Engineer (Large Systems)
Builds
High-performance AI inference and training systems on Graphcore accelerators
Domain
AI compute, hardware acceleration, distributed systems
Deliverable
production ML models
Required skills
Deep learning frameworks (PyTorch/JAX), Python/C++ development, hardware-accelerated deep learning, performance profiling, distributed training/inference, kernel optimization
Preferred skills
MLOps on Kubernetes, LLM production systems, low-precision arithmetic, C++/Triton/CUDA kernel writing, HPC networking (Infiniband/NVLink/RoCE), open-source contributions
Technologies
PyTorch, JAX, Python, C++, Triton, CUDA, Kubernetes, Infiniband, NVLink, RoCE
Responsibilities
Implement and train SOTA ML models optimized for thousands of accelerators; benchmark and profile models to identify bottlenecks; develop deep understanding of the software stack to optimize kernel implementations; test and evaluate new software releases; design and conduct experiments on novel AI methods; collaborate with Research, Software, and Product teams to define and build next-gen AI hardware.
Seniority
Senior, hands-on IC
