Machine Learning Engineer
SPG Resourcing — Leeds, GB
- Published on
About the Role
This position is for an experienced Machine Learning Engineer to join a newly established data science team, primarily focused on building and maintaining the infrastructure to support the full data science lifecycle from data ingestion to model deployment, monitoring, and upgrades within Azure and Databricks environments. Collaboration with data scientists in a cross-functional setting is key, as you will be instrumental in transitioning models from research into production.
Key Responsibilities
- Own and develop deployment frameworks for data science services.
- Maintain oversight of data flow into the data science lifecycle from the wider business data warehouse.
- Oversee automation within the data science lifecycle (dataset build, training, evaluation, deployment, monitoring) during production deployment.
- Automate the data science pipeline from data preparation to deployment.
- Collaborate with cross-functional teams to ensure smooth productionization of models.
- Write clean, production-ready Python code.
- Apply software engineering best practices, including CI/CD and TDD.
Required Skills
- Proficiency in Python, Databricks, and Azure.
- Experience with deployment tools (e.g., AKS, managed endpoints).
- Strong software engineering background, including CI/CD, VCS, and TDD practices.
- Ability to integrate machine learning into business workflows.
Desirable Skills
- Background in quantitative disciplines (math, stats, physics).
- Experience in finance, insurance, or ecommerce sectors.
- Familiarity with machine learning frameworks such as TensorFlow, XGBoost, and SKLearn.
About the Company
SPG Resourcing is committed to fostering an inclusive workplace valuing and benefiting from the diversity of the workforce. If you are interested in this opportunity, please reach out at thomas.deakin@spgresourcing.com.