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Salary
$101k – $263k per year (Estimated)
Location
In office (London)

Confirmed on the employer's own hiring board on Sep 24, 2026. First seen by Alion on Feb 3, 2026.

Overview
Company
Impact
Profile match
MediaTek designs system-on-chip processors for smartphones, televisions and connectivity. Its Dimensity and Helio platforms power hundreds of millions of devices annually. The company is one of the largest fabless chip designers in the world.
Overview

As a Research Engineer, you are expected to contribute to cutting-edge projects that advance both applied and theoretical aspects of AI. This role is ideal for individuals who are passionate about building practical systems from research ideas, thrive in a collaborative environment, and are committed to supporting impactful research through technical excellence.

Our team operates in two main directions:

  • Applying AI to the design and optimization of semiconductors
  • Conducting fundamental research that supports both our applications and the broader sci-entific community

Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models.

Key Responsibilities

  • Implement and test research ideas in machine learning and artificial intelligence
  • Build prototypes and support experiments for team and company projects
  • Collaborate with researchers to translate theoretical models into practical systems
  • Maintain and improve research infrastructure, tools, and workflows
  • Assist in preparing technical documentation and reports
  • Stay up to date with the latest advancements in AI and related fields

Qualifications & Skill Required:

  • Experience implementing machine learning algorithms and techniques
  • Proficiency in programming languages such as Python, C++, or similar
  • Strong problem-solving skills and ability to work both independently and collaboratively
  • Good communication skills, with the ability to document and explain technical work clearly

Preferred:

  • Experience with optimization, reinforcement learning, and/or large language models (LLMs)
  • Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX)
  • Experience building and maintaining research infrastructure or tools
  • Exposure to chip design or applied AI research
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