EU remote
Machine Learning Engineer
About this role
At Optimove, we believe people are capable of more than a single job description. You’re not hired just to fill a position- you’re empowered to shape it, grow it, and make it your own. We call this being Positionless. And Positionless isn’t just our culture. It’s our product. Optimove is the creator of Positionless Marketing, an AI-powered platform that gives every marketer the power to analyze, create, launch, and optimize independently.
The result is faster execution, deeper personalization, and 88% greater campaign efficiency. Recognized as a Visionary in Gartner’s Magic Quadrant, we partner with leading brands like Sephora, Staples, and Entain. Today, more than 500 Optimovers across NYC, London, Tel Aviv, Scotland, Brazil, Estonia, and beyond are building the future of marketing together, in an environment that actively encourages ownership and growth, with two out of every three managers promoted from within.
If you’re looking for a place where you can do more, be more, come grow with us. About the Role As a Machine Learning Engineer, you'll join our Personalize team, helping shape and build the products that let our customers personalise messages across every digital touchpoint. You'll work with text data and with cutting-edge technologies including Large Language Models (LLMs), bringing Accessible Intelligence to our customers across both Personalize and Optimove's overall platforms.
This is a role for an engineer who's ready to own meaningful, medium-sized pieces of our personalisation roadmap end-to-end - from problem framing through to deployment and monitoring - and trusted to do so with minimal oversight. It's not solo delivery: you'll be working closely with a dynamic team spanning ML, MLOps and software engineering, and should be happy to contribute at every level, from early-stage research through to production support.
Role & Core Responsibilities Own the delivery of medium-sized ML features end-to-end within Personalize - problem framing, data preparation, model build/train, evaluation, deployment and monitoring - to predictable timelines. Develop predictive ML models for classification, ranking and personalisation, working with our text data. Leverage LLMs and other state-of-the-art techniques to enhance product capabilities. Operationalise models as APIs across real-time and batch environments.