Job Specifications
Job Title: Senior Machine Learning Engineer
Location: London, 3 days p/w onsite
Salary: £89,000 + Bonus
My client are a global, independent digital-focused research and analytics organisation operating across EMEA, North America, and APAC. Their work combines media strategy, data science, qualitative research, and engineering to help clients make confident, data-driven decisions.
The Team
You will be an integral member of the Product & Engineering and Data Science teams.
The structure empowers individuals and creates meaningful scope to contribute and influence outcomes.
Teams collaborate closely across Data Science, Research, Engineering, and Finance in multiple regions.
The culture places strong emphasis on honesty, fairness, curiosity, and continuous learning.
Multidisciplinary expertise and knowledge sharing are core to how the teams operate.
The Role
Co-develop machine learning models with Data Scientists from experimentation through to production, contributing to architecture, training strategy, tuning, and evaluation.
Design, build, and evaluate ML models (e.g., classification, regression, NLP, clustering) to address business challenges, owning the full development lifecycle.
Lead experimentation cycles, including A/B testing, benchmarking, and performance evaluation against business KPIs.
Build and maintain pipelines and frameworks for data versioning, feature engineering, and automated model training within a cloud environment.
Collaborate with Engineering and Data Science teams to organise and optimise model-related data while balancing performance and accuracy needs.
Lead ML engineering tasks including feature engineering, model optimisation, model selection, and integration into production systems.
Essential Skills
6+ years’ experience as a Software Engineer or ML Engineer.
Strong, hands-on experience with GCP (Google Cloud Platform)
Strong understanding of the ML lifecycle and experience using deployment or serving frameworks such as TensorFlow Serving or similar.
Hands-on experience building, training, and evaluating ML models (classification, regression, NLP, time series, etc.).
Solid understanding of statistical modelling, experimental design, and model evaluation metrics (precision, recall, AUC, RMSE, etc.).
Proficiency in Python with strong experience using ML libraries (TensorFlow, PyTorch, scikit-learn).
Expertise with relational databases, especially PostgreSQL, including advanced schema design and query optimisation.
Familiarity with CI/CD, containerisation (Docker), and orchestration tools (Kubernetes).
Strong numerical and analytical skills.
Excellent written and verbal communication skills, with a proactive and collaborative approach.
Desirable
Practical experience working with large language models (LLMs) in data or ML pipelines.
Experience with DuckDB or columnar file systems such as Apache Parquet.
Experience with DBT or similar data transformation frameworks.
Experience with model monitoring or explainability frameworks.
Experience with ML experimentation and tracking platforms (e.g., Weights & Biases, Neptune, MLflow Tracking).
Research experience or an applied ML portfolio demonstrating end-to-end model development.
Experience mentoring colleagues and driving cross-functional process improvements.
About the Company
Recruitment Services… all grown up!
Talent Acquisition can be a messy business, and recruiting top talent is getting tougher and tougher – especially for tech roles.
We set up Revoco to turn a fresh page in our industry’s story by demanding absolute integrity from everything we do, with complete transparency to back it up.
The world has moved on and we’ve moved with it – utilising the best technology and tools available to provide a transparent, insightful, and efficient service for our clients.
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