10 days ago
London, United KingdomSenior
Responsibilities
- Design, train, optimise, evaluate, and monitor predictive, temporal, embedding-based, NLP, and LLM models.
- Productionise and deploy machine learning models reliably at scale in client environments.
- Build and integrate embedding pipelines, RAG workflows, agentic systems, and NLP models.
- Own versioned and validated data flows, schema design, SQL optimisation, data transformations, and cohort logic.
- Lead modelling and data engineering work on client projects and resolve complex modelling and pipeline issues.
- Configure OneView components linked to modelling outputs and feed engineering improvements back into the platform.
- Act as a machine learning and AI subject-matter expert, mentor colleagues, and create reusable documentation and components.
Requirements
- 3–5+ years of experience in machine learning engineering, taking models from development into production.
- Strong Python skills and experience with modern machine learning frameworks and tree-based, temporal, NLP, or LLM-based models.
- Experience building reproducible training and evaluation pipelines and containerising and deploying models, such as with Docker and FastAPI.
- Strong SQL skills and knowledge of relational databases, schemas, data transformations, and preparing data for model training and scoring.
- Hands-on experience with embeddings, vector databases or RAG workflows, and NLP or sequence models applied to real-world datasets.
- Experience delivering technical work to clients or stakeholders, defining data requirements, and troubleshooting in real time.
- Clear communication skills and the ability to explain technical concepts simply while collaborating with data scientists, engineers, and consultants.
- Experience with Azure ML, AKS, or similar cloud environments is beneficial.
- Experience with public-sector datasets or analytical workflows is beneficial.
Benefits
- 12-month fixed-term contract with potential to become permanent.
- Hybrid London-based role requiring office attendance 1–2 days per week, with some travel for on-site client engagements.
- Competitive salary reviewed annually.
- Training and development opportunities.
- 25 days of annual leave plus bank holidays.
- Company pension and private medical insurance.
- Enhanced parental leave, cycle-to-work scheme, flu vaccinations, eye test and VDU glasses contribution.
- Employee Assistance Programme, mental health and wellbeing support, remote GP access, counselling and therapy, physiotherapy, and medical second opinions.
Categories
Data EngineeringML Engineering
