Graphcore
Visit websiteSenior Machine Learning Engineer
Salary not disclosedHybrid
- Engineering
- London
- Full time
- Today
About the role
The Applied AI team at Graphcore is looking for a Senior Machine Learning Engineer to help scale state-of-the-art AI models across thousands of accelerators. You will contribute to advancing AI technology by developing and optimizing models for specialized hardware, working on large-scale systems where performance is critical. This role offers visibility across the entire pipeline from novel accelerator hardware to AI applications.
Responsibilities
- Implement and train state-of-the-art machine learning models and optimize for performance, accuracy and scalability across systems comprising 1000s of accelerators.
- Benchmark and profile ML models to identify performance bottlenecks.
- Develop deep understanding across the software stack in order to optimize kernel implementations.
- Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
- Design and conduct experiments on novel AI methods and evaluate results.
- Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
- Engage with AI community and keep in touch with the latest developments in AI.
Required skills
- Machine Learning
- PyTorch
- JAX
- Python
- C++
- Deep learning
- Hardware-accelerated deep learning
- Performance optimization
Nice to have
- MLOps
- Kubernetes
- Large language models
- Efficient computing
- Low-precision arithmetic
Qualifications
- Bachelor's degree in Machine Learning, Computer Science, Maths, Data Science, or related field
- Master's degree in Machine Learning, Computer Science, Maths, Data Science, or related field
- PhD in Machine Learning, Computer Science, Maths, Data Science, or related field
- Equivalent practical experience
About the Company
Graphcore is a technology company focused on developing specialized hardware and software stacks for AI applications, aiming to ensure their technology works seamlessly with the AI ecosystem at scale.