Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Workflow Engineer

G-Research
London
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Research Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

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

We are looking for exceptional engineers to help us build out a mature ML research and deploy pipeline as part of our ML Workflows team

This is an exciting role. You will develop greenfield solutions to meet highly complex ML interdependency requirements. Where off-the-shelf tools fall short, you’ll build custom solutions to define best practice across quantitative research.

Future projects include:

  • Implementing best practice feature and model stores
  • Properly versioning features, data and models
  • Improving inference compute utilisation via model serving
  • CI/CD for ML
  • Reliably fitting models with complex job dependency graphs
  • Robustness in production, including validation and monitoring

Who are we looking for?

You will be an intelligent, pragmatic and capable engineer. You will be comfortable working collaboratively to quickly get to grips with the widely varying requirements across different teams.

You will bring industry experience to the table, helping us to apply best practice and drive improvements across our ML operations.

The ideal candidate will have the following skills and experience:

  • An appreciation of good architecture and MLOps best practice
  • The ability to collaborate with, and influence, technical and non-technical people
  • A passion for end-to-end ownership of solutions, from articulation to delivery
  • Proven ability to engineer high-quality software
  • Effective decision-making, with a focus on the mid to long term
  • Value orientated and able to independently prioritise

Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.

Why should you apply?

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

.
#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.