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AI Engineering Intern

Why join our team
Industry-leading compensation
A culture that supports your success
Talent development
Relocation support
Comprehensive benefits
  • Software Engineering
  • London

Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips?

G-Research is a leading quantitative research and technology firm, with offices in London and Dallas.

We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.

This is a role based in our new Soho Place office – opened in 2023 – in the heart of Central London and home to our Research Lab.

The role

  • Dates: 30 March 2026 – 18 September 2026 or 29 June 2026 – 18 September 2026
  • Working hours: 09:00–17:30
  • Location: Central London

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

Key responsibilities of the roll include:

  • Designing, building and operating platform services in C# and Python, covering feature stores, vector search, prompt management and model hosting and inference
  • Implementing type-safe orchestration workflows using LangGraph and Pydantic
  • Scaling embedding and RAG pipelines to support large, high-throughput workloads
  • Collaborating with research and product teams to productionise AI prototypes
  • Applying best practices in testing, version control, CI/CD and observability
  • Benchmarking and optimising latency, throughput and cost across on-prem GPU clusters and cloud platforms

Who are we looking for?

We value engineers who are energised by complex, systems-level challenges, work fluently across languages and tooling and care deeply about developer experience and platform ergonomics.

You should be comfortable owning services end-to-end, from design docs to production dashboards, and motivated by the opportunity to help shape the foundations of AI development at G-Research.

The ideal candidate will have the following skills and experience:

  • 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

The following experience is beneficial:

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

Why should you apply?

  • Highly competitive compensation plus annual discretionary bonus
  • 30 days’ annual leave
  • Lunch provided (via Just Eat for Business) and dedicated barista bar
  • 9% company pension contributions
  • Comprehensive healthcare and life assurance
  • Informal dress code and excellent work/life balance
  • Cycle-to-work scheme
  • Monthly company events

Location: London
Apply Now
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Alexander Software Engineer

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What our people say

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Mario FPGA Manager

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Sebastian Senior Quantitative Researcher

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Mia Software Engineer

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Yang Quantitative Researcher

"What I like the most about my job is it’s super open. I’m able to work with a lot of folks from other teams, too, such as working closely with engineers and other quantitative researchers."

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Interview process

Online Application

Our assessment process kicks off with our Talent Acquisition team, who will review your application and assess your fit for the role.

Stage One: Technical Interview

You will meet with a team member – or take a remote test – where your technical abilities will be put to the test.

Stage Two: Behavioural Interview

We will set aside technical skills and focus on you.

Stage Three: Further Technical Interviews

Here, we will take a deeper dive into your technical skills and competencies.

Stage Four: Management Interviews

The final stage of our interview process is where you will meet members of your team, your future manager, and functional leadership.

AI Engineering Intern Apply now

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