# AI Systems Researcher/Engineer

**Company:** [Brave](https://hotfix.jobs/companies/brave)
**Location:** London, United Kingdom
**Role:** AI Research
**Skills:** Python, C++, JavaScript, Rust, Machine Learning, PyTorch, TensorFlow, Mlx, Onnx Runtime, Core Ml, TensorRT, Systems Optimization, Computer Networks, Confidential Computing, Open Source
**Posted:** 2026-08-26

> Research and engineer AI systems, optimizing and evaluating machine-learning models and on-device performance across desktop and mobile products. The role requires software development experience, systems and networking knowledge, and expertise with modern ML frameworks, privacy, and security.

## Job Description

## Responsibilities
- Shape and improve AI systems performance evaluations and optimizations across desktop and mobile.
- Work on browser machine-learning models, novel applications, on-device AI agents, and performance evaluations.
- Collaborate with privacy and security researchers to address risks associated with AI.
- Implement data-driven products and create and deploy mobile, desktop, and other systems.
- Contribute in an open-source setting and apply a disciplined, scientific approach to understanding system behavior.

## Requirements
- Experience with software development practices and one or more of Python, C++, JavaScript, or Rust.
- Background in AI systems research and performance evaluation.
- Expertise optimizing and evaluating ML models and/or privacy and security technologies for on-device performance.
- Experience with modern ML frameworks such as PyTorch, TensorFlow, MLX, ONNX Runtime, Core ML, or TensorRT.
- Broad understanding of systems and networks.
- Ability to create and deploy mobile and desktop applications and systems.
- Passion for protecting user privacy and security.

## Nice to Have
- ML systems experience, including pipelines and performance evaluation.
- Open-source projects focused on mobile or desktop systems optimization.
- Experience with confidential computing and security/privacy protocols.
- Ph.D. in computer science.
- Strong publication record in systems, performance, or ML.
- Industry experience.

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