7 months ago
London, United KingdomMid Level
Responsibilities
- Evaluate alternative accelerators and the latest hardware and software for machine-learning workloads.
- Investigate multi-node distributed training and networking trade-offs.
- Optimize model inference for latency or throughput.
- Evaluate and optimize storage technologies for bandwidth.
- Apply profiling, optimization, HPC, and modern machine-learning techniques to engineering challenges.
- Design quick scripts for proofs of concept and more complex systems when appropriate.
- Collaborate with quantitative researchers, ML engineers, engineering teams, external partners, and vendors.
- Provide constructive feedback to vendors and present results effectively to stakeholders.
Requirements
- Postgraduate degree in machine learning or a related field, or commercial experience building machine-learning models at scale.
- Exceptional candidates with a demonstrable record of success in online data-science competitions such as Kaggle may be considered.
- Strong object-oriented engineering skills.
- Experience with Python, PyTorch, and NumPy is desirable.
- Expertise in some combination of advanced optimization methods, modern machine-learning techniques, HPC, profiling, or model inference.
- Ability to work independently and in small teams, engage with vendors, explore new technologies, and communicate results effectively.
- Finance experience is not required.
Benefits
- Highly competitive compensation plus an annual discretionary bonus.
- Lunch provided via Just Eat for Business and a dedicated barista bar.
- 30 days of annual leave.
- 9% company pension contributions.
- Informal dress code and work/life balance support.
- Comprehensive healthcare and life assurance.
- Cycle-to-work scheme.
- Monthly company events.
- Inclusive work environment with accommodations available for applicants with disabilities or special needs.
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