AI Research Engineer (Model Training)

StackOne; Greater London; Hybrid; GBP 65,000 - 85,000; Full time

Job summary

A leading AI startup in Greater London is seeking an AI Research Engineer to enhance large-scale model performance through fine-tuning and experimentation. This role involves managing model training infrastructure and synthesizing datasets, focusing on real-world applications. Ideal candidates will have a strong background in deep learning, experience with distributed training jobs, and a collaborative spirit within a dynamic team. The position offers a hybrid work setup with attractive benefits including private health insurance and employee share options.

Benefits

25 days holiday plus additional days based on tenure

Employee share options plan

Private health insurance

Health fitness and gift card discounts

£1000 for home office setup

Annual team offsite to sunny spots

Cycle2Work and Electric Cars scheme

Qualifications

• Experience running large-scale distributed training jobs.
• Understanding of synthetic data techniques and dataset pipeline design.
• Desire to work in a fast-paced startup taking ownership of projects end-to-end.

Responsibilities

• Own the full lifecycle of model fine-tuning projects.
• Design and manage synthetic data generation workflows.
• Build and maintain large-scale training infrastructure.

Skills

Python

C / C++

Fortran

R

Data Mining

MongoDB

Education

Background in deep learning with emphasis on LLMs

Tools

Data Modeling

Matlab

SAS

Job description

About StackOne :

StackOne is the AI Integration Gateway for SaaS products and AI Agents. Backed by GV and Workday Ventures ($24M raised) we help builders of SaaS platforms and AI Agents orchestrate hundreds of scalable accurate and enterprise-grade integrations. Our platform combines 25000 pre-mapped actions on 200 connectors an AI-powered integration development toolkit plus security by design : a real-time architecture managed authentication and permissions and end-to-end observability.

Join us on our fast trajectory to build the future of agentic integrations.

With an AI-native integration toolkit that delivers real-time execution managed authentication granular permissions and full observability all built with safety at its core were now doubling down on AI R&D & creating our own lab to push the boundaries of tool calling for agents : training specialized LLMs designed to outperform general‑purpose models in what matters most : precision reliability and safety in agentic execution.

About the role

Youll help build a world where users of any agents can integrate with the tool of their choice in one click thanks to StackOne.

We are looking for an AI Research Engineer with deep expertise in large‑scale model fine‑tuning dataset curation and training infrastructure . Unlike our AI Engineer role which focuses on applying and productionizing existing LLMs and agent frameworks this role is focused on pushing model performance through fine‑tuning synthetic data pipelines and large‑scale experimentation .

You will own design and run experiments on cutting‑edge architectures manage distributed training clusters and help curate & generate high-quality datasets. This role sits closer to the research / ML infra side than product engineering but with a strong mandate for applied production‑ready results.

In this role you will work with wider AI team of StackOne (comprising of other researchers and engineers) and report directly to the CTO.

Responsibilities

Own the full lifecycle of model fine‑tuning projects (objectives dataset prep training eval deployment handoff).

Design and manage synthetic data generation workflows to augment real‑world datasets.

Build and maintain large‑scale training infrastructure (multi‑GPU / TPU clusters orchestration optimization).

Develop tools for dataset curation labeling filtering and augmentation .

Conduct benchmarking and evaluations to measure fine‑tuning impact.

Collaborate with the rest of the engineering team to integrate fine‑tuned models into production stacks.

Stay ahead of research in parameter‑efficient fine‑tuning synthetic data and LLM training.

What were looking for

Background in deep learning with emphasis on LLMs .

Experience running large‑scale distributed training jobs

Understanding of synthetic data techniques and dataset pipeline design.

Proficiency in evaluating LLMs with quantitative metrics and human evals .

Desire to work in a fast‑paced startup taking ownership of projects e2e and bias towards shipping.

(Preferred) Contributions to open‑source ML libraries or published research in applied ML / LLM fine‑tuning.

Benefits

25 days holiday 1 additional day holiday per year of tenure

Participation in the companys employee share options plan

Private health insurance (including dental & optical)

Health fitness and gift card discounts

1000 for your home office set up 500 / year top‑up

Paid lunch in the office

Annual team offsite to sunny spots (last ones were in Spain and Portugal )

Join one of Europes fastest-growing startups

Work with a veteran team of ex‑employees of Google Microsoft Oracle Coinbase JP Morgan and more

Cycle2Work and Electric Cars scheme

Hybrid work set up - typically 2d in the office

Ready to help us change the game for SaaS integrations Get in touch and lets chat!

We believe diversity drives innovation. We encourage individuals from all backgrounds to apply. As an equal‑opportunity employer we celebrate diversity and are committed to creating an inclusive environment for all employees.

Key Skills

Python,C / C++,Fortran,R,Data Mining,Matlab,Data Modeling,Laboratory Techniques,MongoDB,SAS,Systems Analysis,Dancing

Employment Type : Full-Time

Department / Functional Area : Engineering

Experience : years

Vacancy : 1