Machine Learning Jobs

Harnham - Data and Analytics Recruitment · France · €130,000 – €150,000 pa

Define the technical direction of large-scale production ML systems while remaining hands-on across the full model lifecycle, leading end-to-end initiatives in recommendation systems, audience targeting, bidding optimisation and customer lifecycle modelling. Work directly alongside the CTO in a high-scale real-time AdTech environment, combining technical strategy, platform engineering and applied ML as an individual contributor leader rather than a people manager.

Harnham - Data and Analytics Recruitment · London · £90,000 – £120,000 pa

Embedded in portfolio companies to deliver data science and machine learning initiatives, partnering with C-suite stakeholders to define problems with measurable commercial value. You own projects end to end, from discovery and modelling through deployment and scaling, across use cases like pricing, sales optimisation and fraud reduction. The role sits in a deployment team within an investment and private equity ecosystem, balancing technical rigour with pragmatic delivery.

Ocado · Kraków, Poland

Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training to serving, monitoring and cost management, while coaching others and shaping reusable platform building blocks.

VIQU IT · London · £75,000 – £80,000 pa

Design and deliver deployable AI/ML models spanning forecasting, propensity, churn and customer segmentation, owning end-to-end workflows from feature creation to ML Ops deployment and monitoring. Architect bespoke datasets from structured and semi-structured sources, visualise results into decision tools, and mentor junior data scientists in a cloud-native, AI-first SaaS company.

Harnham - Data and Analytics Recruitment · London · £75,000 – £85,000 pa

Own the ML Ops function within a growing AI and data organisation, building and maintaining production-grade ML orchestration pipelines with Dagster, Airflow or Prefect. Deploy, monitor and scale ML and LLM-powered services on Kubernetes using Terraform or Bicep, with strong CI/CD and observability practices, working closely with data scientists and client-facing teams.