Full-Time

Research Engineer

Game Theory & Multi-Agent Systems

Posted on 9/27/2025

DeepMind

DeepMind

1-10 employees

AI research organization pursuing safe AGI

No salary listed

London, UK

In Person

Category
AI & Machine Learning (2)
,
Required Skills
Python
Pytorch
Pandas
NumPy
C/C++
Data Analysis
Requirements
  • Master’s degree or PhD in Computer Science or a related technical field.
  • 5+ years of software development experience using Python or C++.
  • Experience with deep learning frameworks, such as JAX (preferred) or PyTorch.
  • Experience with standard analysis and scientific computing libraries: numpy, pandas, and matplotlib. Familiarity with scipy, sklearn, and altair is considered a plus.
Responsibilities
  • Creating novel learning algorithms and complex game-theoretic models, with a primary focus on performance and scalability in JAX.
  • Building and maintaining large-scale simulation platforms and end-to-end research pipelines to run experiments on Google DeepMind’s cutting-edge infrastructure, including massive TPU pods.
  • Partnering deeply with Research Scientists to transform mathematical concepts and research hypotheses into robust, production-quality code and reproducible experiments.
  • Leading the engineering direction for complex research projects, establishing best practices for code quality and maintainability, and mentoring junior engineers on the team.
  • Optimizing every part of the research workflow, from data processing and model training to results analysis, to drastically accelerate the pace of discovery.
Desired Qualifications
  • PhD with a research focus on Machine Learning, Reinforcement Learning, or Multi-Agent Systems.
  • Deep expertise building and optimizing complex systems in JAX.
  • Experience training large-scale models on accelerators (TPUs, GPUs) in a distributed environment.
  • A strong background in algorithmic game theory, multi-agent reinforcement learning, or computational economics.
  • A track record of leading complex software projects and a passion for enabling groundbreaking research through world-class engineering.
  • Experience working with language models such as designing agentic harnesses, memory retrieval, or fine-tuning.

DeepMind conducts research in artificial intelligence to advance general problem-solving capabilities with safety and ethics guiding every project. It develops AI systems and learning algorithms that can tackle complex tasks, such as diagnosing eye diseases, reducing data center energy use, and predicting 3D protein shapes. These products work by learning from large datasets and optimizing models to perform specialized tasks, often through deep neural networks and reinforcement learning, then deploying the resulting systems to assist scientists, doctors, and engineers. What sets DeepMind apart is its emphasis on rigorous fundamental research published in top journals, a strong safety/ethical framework, and collaboration on real-world scientific challenges, rather than just commercial applications. The company’s long-term goal is to solve intelligence and build more general, capable problem-solving systems that can help society address major scientific and humanitarian problems.

Company Size

1-10

Company Stage

Acquired

Total Funding

$533M

Headquarters

Thessaloníki, Greece

Founded

2010

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Simplify's Take

What believers are saying

  • GraphCast excels in extreme weather prediction, partnering with disaster agencies.
  • AlphaFold collaborates with DNDi on Chagas and Leishmaniasis therapeutics.
  • Open GraphCast deployment since September 2024 enables enterprise licensing.

What critics are saying

  • Top AI talent exits DeepMind due to Google merger bureaucracy.
  • Isomorphic Labs secures Eli Lilly and Novartis drug discovery deals.
  • NVIDIA's PhysicsNeMo reimplements GraphCast, commoditizing the technology.

What makes DeepMind unique

  • AlphaFold predicts protein structures, catalyzing biology progress since 2021.
  • GraphCast delivers 90% accurate 10-day weather forecasts in under one minute.
  • AlphaGo defeated Go champion Lee Sedol in 2016 using reinforcement learning.

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