Senior Research Engineer in England

Contract Type:
6 month contract outsourced via agency on an hourly rate
Location:
Egham
Hybrid
: 3 days onsite (minimum) and 2 days working from home
Rate:
Very much dependant on level of experience.
Key responsibilities include:
Performance Optimization:
Profile and debug performance bottlenecks at the OS, runtime, and model levels.
Model Deployment:
Work across the stack—from model conversion, quantization, and optimization to runtime integration of AI models on-device.
Toolchain Evaluation:
Compare deployment toolchains and runtimes for latency, memory, and accuracy trade-offs.
Open-Source Contribution:
Enhance open-source libraries by adding new features and improving capabilities.
Experimentation & Analysis:
Conduct rigorous experiments and statistical analysis to evaluate algorithms and systems.
Prototyping:
Lead the development of software prototypes and experimental systems with high code quality.
Collaboration:
Work closely with a multidisciplinary team of researchers and engineers to integrate research findings into products.
We not require a PhD holder this time which is unusual for the AI Team.
We\’re looking for someone with:
Technical Expertise:
Strong OS fundamentals (memory management, multithreading, user/kernel mode interaction) and expertise in ARM CPU architectures.
Programming Skills:
Expert proficiency in Python and Rust, with desirable knowledge in C and C++.
AI Knowledge:
Solid understanding of machine learning and deep learning fundamentals, including architectures and evaluation metrics.
Problem-Solving:
Strong analytical skills and the ability to design and conduct rigorous experiments.
Team Player:
Excellent communication and collaboration skills, with a results-oriented attitude
Desirable Skills:
Experience with ARM 64-bit architecture and CPU hardware architectures.
Knowledge of trusted execution environments (confidential computing).
Hands-on experience with deep learning model optimization (quantization, pruning, distillation).
Familiarity with lightweight inference runtimes (ExecuTorch, , Candle).
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