Graphcore's ML QA team is hiring a Senior ML Engineer to validate the ML software and hardware stack that powers AI compute. You will test, benchmark, and debug complex ML systems by running open-source models, building automated benchmarking pipelines, and targeting numerical precision, quantization, attention mechanisms, and distributed execution. This hands-on role focuses on making AI systems run reliably on ambitious infrastructure rather than designing new models.
Responsibilities
Test, benchmark, and validate Graphcore's ML software and hardware stack before customer release.
Run open-source models and build automated benchmarking pipelines.
Create targeted tests for low-level ML behavior including numerical precision, quantization, attention mechanisms, distributed execution, and model subgraphs.
Expose regressions, correctness issues, and performance limits across frameworks, models, and execution environments.
Collaborate with software, infrastructure, and hardware teams to raise the quality bar.
Requirements
Strong experience in machine learning or ML-adjacent software engineering roles.
Solid grasp of neural networks, training, inference, numerical precision, and performance trade-offs.
Hands-on experience with PyTorch, TensorFlow, JAX, Triton, or similar ML frameworks and tools.
Strong Python skills for automation, experimentation, benchmarking, and reporting.
Graphcore is a semiconductor company that develops accelerators for AI and machine learning, specifically its proprietary Intelligence Processing Unit (IPU) designed for massively parallel processing of machine learning models. The company, now a subsidiary of SoftBank Group, focuses on enabling breakthroughs in machine intelligence.