Research Engineer, Tool Use, DeepMind

Software Careers

Greater London

Vor Ort

GBP 80.000 - 110.000

Vollzeit

14 Tage+

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Zusammenfassung

DeepMind in London, UK is seeking a Research Engineer focused on tool use to advance AI systems. You will write and test production code, participate in design reviews, and help shape scalable engineering workflows.

You will review peers’ work, contribute to docs and tutorials, and triage issues affecting hardware, networks, or services, collaborating with research and engineering teams to turn ideas into reliable solutions.

Qualifikationen

  • Experience writing and testing production-grade software for AI/ML systems.
  • Familiarity with ML model training and evaluation, and scalable data pipelines.

Aufgaben

  • Write and test product or system development code.
  • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  • Review code developed by other developers and provide feedback to ensure best practices.
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Triage product or system issues and debug/track/resolve by analyzing sources and impact on systems.

Kenntnisse

Software development
Programming languages
Machine learning models
Model training
Engineering workflows
Data analysis at scale
Data visualization
Data ingestion pipelines
Large language models
AI agents

Tools

JAX
PyTorch

Jobbeschreibung

# Research Engineer, Tool Use, DeepMindat DeepMind • London, UKBack to jobs1. Home2. Jobs3. UK4. Research Engineer, Tool Use, DeepMind—D## Research Engineer, Tool Use, DeepMindDeepMind10Artificial Intelligence, Machine Learning, Research, Software EngineeringFull-timeLondon, UKApply Job### Job DescriptionAt Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers. Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer various learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Responsibilities: Write and test product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.### Skills Required* Software Development* Programming Languages* Machine Learning Models* Model Training* Engineering Workflows* Data Analysis at Scale* Data Visualization* Data Ingestion Pipelines* Large Language Models (LLMs)* AI Agents* Tools* JAX* PyTorch
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