Senior Research Engineer

2 days ago

Egham, Surrey, United Kingdom microTECH Global LTD Full time

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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