Senior ML Engineer / ML Lead

Permanent employee, Full-time · Hybrid, London, Remote

95,000 - 160,000 £ per year

Your mission

To build and lead Track Titan's ML capability at a pivotal moment for our AI direction. You will take our unique dataset – millions of laps of racing telemetry across thousands of car/track combinations – and turn it into the foundation of a genuinely new kind of AI coaching platform. You'll be hands-on technically from day one, while growing and guiding a small team that will define how we do ML at Track Titan.

What you will do:

Build the telemetry understanding layer. Design and train the models that learn meaningful representations from racing telemetry – self-supervised encoders, sequence models, embedding systems. This is the technical foundation everything else builds on, and you'll own it end-to-end: from problem formulation through architecture decisions to production deployment.
Evolve our coaching intelligence. We have an existing coaching system and a massive dataset – your job is to unlock the next level. You'll introduce new approaches to problems like mistake identification and time-loss attribution that scale with our data, moving us from domain-engineered solutions toward learned models that generalise across cars, tracks, and driving styles.
Set the ML technical direction. Evaluate approaches, define the model and data strategy, and make the architectural decisions that will shape our ML stack for years. Establish the practices that make ML work reliable – experiment tracking, evaluation harnesses, reproducibility. You'll work closely with the CTPO (who has deep AI/ML experience) to pressure-test ideas and align ML work with product and business priorities. You'll have strong opinions, the technical depth to back them up, and the humility to change your mind when the data says otherwise.
Lead and grow the ML team. You'll lead a small, growing ML team and be responsible for raising the bar: code quality, experimentation rigour, review culture, and technical development. As we scale, you'll shape what the ML function looks like and play a key role in hiring the people who join it.
Ship models that reach users. Research taste matters, but so does pragmatism. You'll balance long-term foundational work with near-term product impact, finding the stepping stones where better models directly improve insights and coaching quality for hundreds of thousands of drivers. You'll define clear contracts with the product engineering team and own ML systems through to production.

Your profile

5+ years of hands-on ML engineering experience, with meaningful time spent on self-supervised learning, representation learning, or sequence modelling. You've trained models on real-world data at scale – not just reproduced papers or done abstract research.
Deep experience with modern sequence modelling. You've worked with transformers on sequential data – NLP, time-series, sensor data, trajectories, audio, or similar. You understand the design choices (tokenisation, patching, positional encoding, multi-scale architectures) and have opinions about when they matter and when they don't.
Strong embedding and retrieval intuitions. You've built systems where learned representations are the product – similarity search, clustering, retrieval, recommendation. You understand contrastive learning, evaluation of embedding quality, and the practical challenges of making representations useful downstream.
Production ML experience. You've taken models from research to production and dealt with the realities: data quality, pipeline reliability, monitoring, and the gap between offline metrics and real-world performance. You don't need a separate team to productionise your work.
Technical leadership experience or clear readiness for it. You've mentored engineers, led technical direction for a team or project, or set standards that others follow. You don't need to have managed a team formally, but you should be ready to – and excited about raising the level of the people around you.
A cross-domain thinker. We're building something genuinely new, and we want someone who gets energised by that, who can draw on ideas from diverse fields like NLP, audio, robotics, or control theory and apply them with fresh eyes. If you've worked across multiple domains or brought techniques from one field to another, that's exactly the profile.
Excellent written communicator. As a partially distributed, async-first team, writing is how we think together. Technical proposals, experiment write-ups, architectural decisions – you express complex ideas clearly and concisely, and you engage constructively with others' writing.
Motorsport passion or experience is a strong plus – but not a firm requirement. Some of our team are professional racing drivers. Others came in as fans or curious newcomers and went deep. What matters is genuine curiosity and a willingness to learn. If you join, you'll be expected to immerse yourself in this world and grow your understanding on things like vehicle dynamics. But we don’t expect you to be an expert on this (we have a lot of existing domain expertise on the team that you can tap into).
A research background (PhD or equivalent depth) is valued but not required. What matters is the depth of your technical intuition and your ability to formulate problems well – qualifications are secondary.
Fluent with AI tools in your daily workflow. You already use LLMs and AI-powered tools to move faster – whether for research, writing, analysis, or prototyping. We're an AI company and we expect everyone to work like one.

What this role is not:

A pure research position – you'll publish if it makes sense, but the goal is product impact
A prompt engineering role – we mean real modelling, not LLM wrangling
An MLOps or platform engineering role – you'll care about infrastructure, but your focus is modelling and representation learning
Purely executing someone else's technical vision – you'll shape the direction, working closely with a technically deep CTPO who will both challenge and support you

Why us?

A genuinely unprecedented ML challenge. Millions of laps. Thousands of car/track combinations. Multivariate time-series with causal structure, cross-domain transfer problems, and a direct line from better representations to better coaching. If you've been looking for a dataset and problem that nobody else has, this is it.
Build the ML function from the ground up. We have a small foundation, but you won't inherit a large legacy system you can't change or a team culture you didn't shape. You'll define how we do ML – the architecture, the practices, the team – at a moment where those decisions compound.
Work with leadership that speaks your language. Our CTPO has deep AI/ML experience (previously led Applied AI at a public tech company) and will be a genuine technical partner – not someone you need to translate for. We also have a team that’s extremely deep and knowledgable in the motorsport domain.
Flexible location. We have a great London HQ, and while we would love to have you in London, we are flexible (and our existing team is distributed). Europe is generally no problem, and for exceptional candidates global remote could also be negotiable on a case-by-case basis for this role.
Join the only motorsport startup in the world backed by tier-one VCs
Work on cutting-edge tech, campaigns, and partnerships that reach users across the globe 24/7
Join a team of fellow motorsport fans and sim racers who have backgrounds in top startups, sports data science, tier-one consulting, and professional motorsport
Quarterly learning day and budget
Generous options package as a key early employee
Private pension (for UK employees)
Private health insurance (for UK employees)

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About us

Want to build the "Strava for Motorsport"?

At Track Titan, we are building the “Strava for Motorsport” by combining AI driver coaching with community and social features.
With a user-base in the hundreds of thousands and millions of laps processed, Track Titan is already the dominant simracing coaching platform and we have big plans to go further. We are a team of fifteen backed by some of the world’s best VCs, strategic investors such as Porsche and have recently launched integrations with key industry players such as MOZA and Fanatec. This is your one-time chance to build a venture-scale startup in the most exciting sport on the planet.

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We are looking forward to hearing from you!

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