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Paid Internship
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Time Spent
Required Degree
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22Open Positions

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AI Engineering Intern

G-Research
Found 2 months ago
Location
London, United Kingdom
Time
Full-time
Work Mode
On-site
Salary
Highly competitive compensation plus annual discretionary bonus
Visa Help
Not disclosed
Last Verified
2 months ago

Education

  • Bachelor

Skills & Qualifications

Technical Skills

  • C#
  • Python
  • distributed systems
  • LangGraph
  • LangChain
  • Pydantic
  • FastAPI
  • MCP
  • RAG pipelines
  • Agentic workflows
  • GPU scheduling
  • model-parallel inference
  • vLLM
  • TensorRT-LLM

Soft Skills

  • complex, systems-level challenges
  • developer experience
  • platform ergonomics
  • owning services end-to-end
  • testing
  • version control
  • CI/CD
  • observability
  • collaboration

Job Description

We’re seeking a Software Engineering Intern to join our Core AI sub-team within the AI Engineering Group at G-Research. The Core AI team builds and evolves the foundational platforms behind every Generative AI initiative within the firm, from RAG services to tooling that improves developer experience across quant and engineering teams. As part of this team, you’ll contribute to the design and delivery of scalable, reliable and secure infrastructure that enables researchers, data scientists and engineers to experiment and deploy AI solutions safely and at speed. Your work will span critical projects and workstreams, including distributed systems development, LLM orchestration and inference, RAG service integration and leading the drive for internal adoption of third-party AI technologies

Requirements

  • A degree in Computer Science, Engineering or a related field
  • Strong production-grade programming skills in C# and Python, or equivalent
  • Solid understanding of distributed systems, such as networking, storage, concurrency and fault tolerance
  • Familiarity with AI engineering tooling, such as: LangGraph / LangChain Pydantic FastAPI MCP RAG pipelines Agentic workflows

Related Field

  • Software Engineering

Related Subfield

  • AI/ML/GenAI Engineering

Languages

  • English

Nice to Haves

  • Exposure to GPU scheduling or model-parallel inference (e.g. vLLM, TensorRT-LLM)
  • Contributions to open-source AI infrastructure projects
▶Apply Now

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