Senior Machine Learning Engineer (E3)
Senior ML Engineer builds and operates production AI systems for Ocado’s ecommerce personalization, ranking, and recommendation features using Python, GCP/Vertex AI, and BigQuery.
- Compensation
- PLN 23.6K–PLN 29.9K / mo
- Location
- Krakow, Poland; Wroclaw, Poland
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- ML engineering in production: demonstrated experience owning the full Data Science lifecycle — data, training, evaluation, deployment, serving, and ongoing operations — on production systems, not just
- Data fluency: strong working knowledge of data processing tools — BigQuery (SQL), pandas, Dataflow, or equivalents — and the ability to reason about data quality as a first-class concern.
- ML fundamentals: fluency across supervised and unsupervised learning, ranking models, recommendation systems, evaluation metrics, overfitting, and model selection.
- Cloud platform experience: practical experience with GCP (our primary environment — Vertex AI, BigQuery, Dataflow) and AWS, both of which are in use across our platform.
- Python: strong production-grade Python; comfortable in a codebase where your models and services are consumed by other engineers.
- Technical leadership: experience leading the technical design of ML projects, including articulating trade-offs and driving decisions within a team.
Full description
About UsWe are Ocado Group, and we're bringing world-class automation to online grocery. Our Ocado Smart Platform (OSP) combines cutting-edge robotics, AI, and IoT within our advanced CFCs (Customer Fulfilment Centres). We've mastered the single pick, transforming online delivery for our global partners. Join us and be part of a team pushing the boundaries of retail technology.
About the team
Smarties is the Data Science and intelligent personalisation team within the Ecommerce stream at Ocado Technology — the part of Ocado Smart Platform (OSP) that powers the end-customer shopping experience. We build the prediction, ranking, and recommendation capabilities that power smart features across OSP and that product teams integrate into customer-facing journeys.
We are a cross-craft team combining data scientists, software engineers, and ML engineers — a mix of skills that lets us work across the full stack of a smart feature, from data and modelling to production systems.
Our mission is to make smart feature development scalable and self-serve. We turn the hard parts of "smarts" — prediction, ranking, personalisation — into reusable building blocks, proven on our own products first, so that over time any product team can build intelligent features using our platform and our support.
We own and operate a broad portfolio of Data Science systems in production: checkout walk personalisation, order prediction and recommendations, customer intelligence, search and browse ranking, recipe discovery, and the web analytics data pipeline that underpins measurement across Ecommerce. We are in an active phase of evolution — consolidating shared capabilities, reducing complexity, and opening space for new initiatives — while progressively shifting toward a platform model where product teams build on shared Data Science capabilities.
Underpinning all of this is data quality. Smart features are only as good as the data behind them. We treat reliable, well-understood data as a foundation, not a side task — and we actively contribute to raising that standard across Ecommerce.
Ecommerce is also a genuinely good place to be a technical engineer right now. Practically all the way up the reporting line you will find people with strong technical backgrounds who share a vision for what modern software development looks like — including how AI tools and coding assistants are changing what high-quality engineering means in practice. That perspective shapes how we work, what we invest in, and how we develop people.
Job Purpose
A Senior ML Engineer in Smarties brings the engineering perspective to a cross-craft team: raising the bar on how ML systems are built, not just how they perform. This means championing industry best practices across the full ML lifecycle — from experimentation and model design through to serving, monitoring, and cost management — and translating that expertise into systems that are reliable, testable, scalable, and maintainable in production.