Research Engineer, Data Infrastructure in London

Research Engineer, Data Infrastructure in London

London Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
M

At a Glance

  • Tasks: Build and scale cutting-edge data infrastructure for AI solutions.
  • Company: Join Mistral, a leader in full-stack AI solutions with a collaborative culture.
  • Benefits: Comprehensive benefits package, including healthcare, wellness programs, and relocation support.
  • Other info: Hybrid work model with opportunities for remote candidates in select EU countries.
  • Why this job: Make a real impact in AI by designing massive compute and storage systems.
  • Qualifications: 4+ years in Data Infrastructure or MLOps, proficient in Python and Kubernetes.

The predicted salary is between 80000 - 100000 £ per year.

About Mistral

Mistral provides full‑stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high‑stakes industries like finance, manufacturing, defense, healthcare, and the public sector—co‑creating customized AI systems that they can run on their terms.

Role Summary

The Data Infrastructure team at Mistral AI is architecting the backbone of our frontier model training and fine‑tuning ecosystem. We are building the specialized compute and data fabrics required to power the development of world‑class AI. Our vision is to operate some of the largest compute fleets in production and build data lakes and metadata systems with a roadmap toward exabyte‑scale architecture. We are currently building a high‑performance training platform designed for massive scale across both on‑premise and cloud‑native Kubernetes environments. We are leading a strategic transition from legacy scheduling to modern orchestration, implementing sophisticated multi‑cluster orchestration and cloud‑bursting capabilities to better utilize our global resources and ensure our researchers have seamless access to compute wherever it resides. Our mission is to evolve our current systems into a durable yet flexible platform.

Location: Paris / Warsaw / Zurich / London (hybrid) or remote EU/UK with one hub visit per month.

About The Role

This role focuses on building and operating the next generation of data infrastructure at Mistral AI. You will be a core contributor to our evolution, helping us design and scale massive compute fleets and storage systems designed for high performance and scalability. You will help us move toward a future of decoupled control and data planes, scaling big data compute and storage platforms while ensuring secure and governed data access for MLOps and research. You will take full lifecycle ownership: from architecting the migration away from legacy orchestrators to implementing production‑grade pipelines and participating in on‑call rotations for critical training jobs.

In this role, you will:

  • Build & Scale: Reach the goal of operating massive distributed compute and storage systems.
  • Global Orchestration: Architect and maintain multi‑cluster orchestration layers to optimize workload placement across diverse hardware and regions.
  • Design Future‑Proof Storage: Lead the transition to modern storage formats to handle fine‑tuning datasets at a scale that anticipates exabyte growth.
  • Platform Engineering: Contribute to the development of our internal training platform, ensuring seamless model training and fine‑tuning across Kubernetes and SLURM‑based environments.
  • Metadata & Lineage: Implement and manage systems to provide clear visibility and lineage as our data and model pipelines grow in complexity.
  • Operational Excellence: Use modern deployment workflows to manage cloud‑native deployments, ensuring our data platform can scale by orders of magnitude while remaining reliable and efficient.

You might thrive in this role if you:

  • Have 4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering.
  • Have experience or a strong interest in supporting foundational compute and storage platforms.
  • Are proficient in Python and enjoy solving the brittle data lake problem with modern, columnar storage standards.
  • Are well‑versed in Kubernetes‑native tooling and excited to debug large‑scale distributed systems across multi‑cluster environments.
  • Take pride in building and operating scalable, reliable, and secure systems from the ground up.
  • Are comfortable with ambiguity and the challenges of building high‑scale infrastructure in a rapid‑growth AI environment.

Location & Remote

This role is primarily based at one of our European offices (Paris, London, Warsaw, and Zurich). We will prioritize candidates who either reside there or are open to relocating. We strongly believe in the value of in‑person collaboration to foster strong relationships and seamless communication within our team. In certain specific situations, we will also consider remote candidates based in one of the countries listed in this job posting—currently France, UK, Poland, and Switzerland. In that case, we ask all new hires to visit the local hub: for the first week of their onboarding (accommodation and travelling covered) and then at least 3 days per month.

What we offer

We offer a comprehensive benefits package designed to support your well‑being, growth, and work‑life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location‑specific perks. For the most up‑to‑date details on benefits available in your location, please refer to our Benefits page.

Research Engineer, Data Infrastructure in London employer: mistral

Mistral is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from competitive salaries, equity options, comprehensive health insurance, and visa sponsorship, alongside ample opportunities for professional growth within the rapidly evolving field of AI. Joining Mistral means being part of a forward-thinking team dedicated to making a meaningful impact through strategic partnerships with leading publishers and academic institutions.

M

Contact Details:

mistral Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Engineer, Data Infrastructure in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like mistral!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Research Engineer, Data Infrastructure at mistral.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like mistral.

Apply Directly through Our Website

When you find a suitable opening like Research Engineer, Data Infrastructure at mistral, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Research Engineer, Data Infrastructure in London

Data Infrastructure
MLOps
Infrastructure Engineering
Python
Kubernetes
Multi-Cluster Orchestration
Cloud-Native Deployments

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at mistral, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at mistral. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at mistral

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at mistral!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.