We're not just building an ecommerce platform. We’re reshaping how fashion & lifestyle brands scale globally.

Our API-first, headless SaaS platform supports over 300 brands in delivering localized, high-performance shopping experiences across 120+ countries. Backed by a 50 million SEK investment from the H&M Group, we power leading names like COS, ARKET, & Other Stories, Weekday, Nudie Jeans, and Paul Smith. Brands trust Centra to run operations in 20+ markets - a reflection of the platform’s flexibility and efficiency.

Why Join Centra?

You will build the predictive “brain” of our new Data & Insights platform. New team, greenfield development, everything to play for. Our goal is to help fashion brands make better decisions at scale - from demand forecasting to reducing overstock and returns - through reliable, production-grade machine learning and AI systems. Our AI / ML Engineer makes this a reality by turning high-quality data into intelligent, actionable systems.

This is a senior individual contributor role with technical ownership. You will design and build the predictive and generative capabilities of our Data & Insights module, moving beyond descriptive analytics into forecasting, recommendations, and AI-driven decision support.

You’ll work closely with our Analytics Engineer to build systems that don’t just explain what happened, but predict what will happen next and recommend what to do about it.

What You’ll Do.

• Build forecasting systems. Design, implement, and continuously improve time-series models for demand, sales, and other ecommerce KPIs.

• Develop AI-driven insights. Build generative AI workflows that interpret data and produce clear, useful summaries and recommendations for users.

• Own production ML systems (MLOps). Design and maintain pipelines for training, evaluation, deployment, and monitoring to ensure models remain accurate as data and market conditions evolve.

• Implement context-aware AI (RAG) Build retrieval-augmented systems that incorporate client-specific data, constraints, and business logic into AI outputs.

• Collaborate on data foundations. Work closely with our Analytics Engineer to ensure models are built on reliable, well-structured data.

What We’re Looking For.

• Deep experience building and deploying production-grade ML systems (e.g. forecasting, regression, recommendation systems).

• Strong Python and experience in the modern ML ecosystem (Pandas, Scikit-learn, PyTorch or similar.)

• Hands-on experience working with LLM-based systems including prompting, orchestration, APIs and evaluation.

• Experience productionising ML systems (model lifecycle, monitoring, retraining, performance trade-offs.)

• Solid data engineering fundamentals. You prepare and shape data for ML workloads, not just consume it.

• Strong understanding of data quality and its impact on model performance.

• Ability to make pragmatic technical decisions in a product engineering environment, balancing experimentation with reliability.

You might be a senior ML engineer who enjoys building real-world systems end-to-end, or a product-minded data scientist who wants to move beyond experimentation into production impact. You’re excited by the challenge of turning complex data into intelligent features that customers actually use. Either way, you're excited about a role building a new module within an established company tackling complex problems in the e-commerce space.

Our Recruitment Process.

Introductory Interview: Meet our recruiter, discuss your experience and expectations. (Online, 30–45 min)

Technical Interview: Dive into technical discussions. (Online or onsite 1.5–2h)

Ways of Working Interview: Explore your alignment with our values and meet the team. (Online or onsite, 1h)

Location and Logistics.

This team is Wroclaw based. We operate an office-first, hybrid working model. You can work up to ten days per month remote. We are open to CoE and B2B working.

Equality.

We’re committed to fair, inclusive hiring and to building a team with diverse perspectives. If you need adjustments during the process, please let us know.