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# Research Engineer, Strategic Bets, DeepMind

- **Company:** Google
- **Location:** London, UK
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Secure Coding, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Information Technology
- **Published:** August 8, 2026
- **Apply:** https://eu.experteer.com/career/view-jobs/research-engineer-strategic-bets-deepmind-london-grossbritannien-58831596

## About the Role

turn into robust, scalable systems Tasks * Bachelor's in Computer Science or related field, or equivalent practical experience * 2 years of experience as Research Engineer or Software Engineer * 2 years of Python development experience * 2 years of experience with LLM agents, LLM inference/serving, RL for LLMs, or multi-agent orchestration * Experience building 0-to-1 systems, pipelines, and scalable infrastructure Key requirements *

## Description

Experteer Overview In this role you will help translate cutting-edge AI research into scalable, production-grade systems. You will work closely with research teams to design and deploy large-scale experiments, scaling LLM architectures and inference pipelines. You will build robust tools for multi-agent workflows and evaluation platforms, driving rapid, empirically grounded progress. This position blends research and engineering to advance forecasting and decision-making under uncertainty at scale. Pay / Benefits * Design and own 0-to-1 infrastructure for forecasting systems and multi-agent workflows * Develop and scale training and inference pipelines, including RL methods and reward loops * Build robust tooling and retrieval harnesses for temporal data and secure code execution * Create contamination-immune evaluation platforms for model calibration and coherence * Integrate modern AI coding tools to accelerate prototype-to-production * Collaborate with research scientists to turn ideas into robust, scalable systems Tasks * Bachelor's in Computer Science or related field, or equivalent practical experience * 2 years of experience as Research Engineer or Software Engineer * 2 years of Python development experience * 2 years of experience with LLM agents, LLM inference/serving, RL for LLMs, or multi-agent orchestration * Experience building 0-to-1 systems, pipelines, and scalable infrastructure Key requirements *


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