Staff Machine Learning Engineer

We're looking for a Staff ML engineer to own optimisation across our platform. You'll be the domain authority on how we use data to make campaigns perform better — from how audiences are composed and scored, to how inventory is priced and allocated, to how campaigns are tuned over their lifetime.

The scope is broad: campaign optimisation, audience quality modelling, lookalike improvement, and measurement all fall within your remit. You'll work across teams, identifying which problems to solve, designing the approaches, and owning the models through to production.

This is a hands-on technical leadership role with broad scope and real autonomy. You'll operate across the full platform, with the freedom to identify the highest-leverage problems and design the approaches to solve them. You'll shape what we build and have a seat at the table when we make product and strategy decisions.

Design and build models for campaign optimisation, working across metrics like CTR, CPA, and ROAS using publisher-side signals (cohort membership, contextual data, engagement) combined with advertiser outcome data.

Develop approaches to inventory allocation that account for audience quality, placement value, and supply dynamics.

Own your models end-to-end from conception through production monitoring. You'll work closely with specialist engineers who integrate models into our high-throughput Scala services, SDKs, and data pipelines — you own the logic, they own the infrastructure, with shared accountability for outcomes.

Influence product direction by identifying opportunities, framing feasibility, and bringing evidence to roadmap decisions.

Run experiments and prototypes to validate ideas quickly, then evolve the best ones into production systems.

Direct experience with optimisation or bidding systems in programmatic advertising — within a DSP, SSP, ad server, or comparable platform. You understand the mechanics of how campaigns are priced, paced, and optimised in practice.

Strong applied ML and statistical foundations. You can design, evaluate, and iterate on models — and you know when a heuristic beats a neural network.

Production ML experience. You've built models that run in real systems, not just notebooks. You understand latency, data freshness, feedback loops, and the gap between offline evaluation and online performance.

Fluency with the programmatic ecosystem — bid requests, win notifications, the signals available at decision time, and the differences between publisher-side and buy-side data.

Strong communication skills. You can explain your thinking to engineers, product managers, and leadership, and you're comfortable advocating for a technical direction.

Experience with cross-publisher or cross-supply optimisation.

Familiarity with privacy-constrained environments — cohort-based targeting, clean rooms, working without user-level identifiers.

You're designing optimisation systems for a platform with a genuinely unusual position — deep publisher-side data, privacy-first architecture, and direct activation through SSPs and ad servers. The modelling problems are novel.

Permutive sits right on the supply so you'll have access to signals that nobody in the bid stream sees — engagement, content, behavioural patterns from inside the publisher.

Small team, high ownership, direct impact. No layers between your work and the product .

We take a structured, objective approach to salary-setting, which is based on marketing information, our compensation strategy, and your experience and capability assessed through our interview process. For a typical candidate who meets our requirements, we pay a base salary of £180,000 - £204,000.

Permutive trusts you to manage your time and deliver results. Our hybrid model allows you to choose where you work best, whether in your own productive space or our London (Farringdon) or New York (Union Square) offices. That said, none of us work alone; we are part of a team.

To foster collaboration and connection, teams in these locations come together in person at least once a week and are encouraged to benefit from being in our offices to meet with teams more often. Commercial and customer-facing teams are encouraged to embrace in-person interactions to build lasting relationships with clients and colleagues.

Every Permutive employee gets together in person at the company’s Annual Kick Off for a week in February. Each year’s event promises to be an exciting opportunity for us to come together, reconnect with colleagues, and align on our shared vision for the year ahead.

At Permutive, we’re taking a thoughtful, intersectional, long-term approach to diversity, equity & inclusion. We care deeply about creating an inclusive work environment that allows everyone to flourish, and we are taking continual action to progress in that direction.

We’re committed to hiring people regardless of race, religion, colour, national origin, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, age, neurodiversity status, disability status, or otherwise.