Software Engineering Manager leading engineering teams to transform application landscape at The Hartford. Ensuring systems are stable, performant, and secure with a Hybrid work schedule.
About the role
- Machine Learning Engineering Manager leading a team at Trainline, helping shape sustainable travel technology with innovative AI and ML solutions.
Responsibilities
- Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers
- Ensure delivery of high-quality machine learning models and AI Systems at scale that drive measurable impact for our business
- Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance
- Partner with stakeholders to propose innovative data products that leverage Trainline’s extensive datasets and state of the art algorithms
- Take an active part in our AI and ML community and foster a culture of rigorous learning and experimentation
Requirements
- Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline
- Have leadership experience either through previous management or mentorship
- Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.)
- Have experience productionising machine learning models
- Are an expert in at least one of: predictive modelling, classification, regression, optimisation or recommendation systems
- Have experience with Spark
- Have knowledge of DevOps technologies such as Docker and Terraform and ML Ops practices and platforms like ML Flow
- Have experience with agile delivery methodologies and CI/CD processes and tools
- Have a broad understanding of data extraction, data manipulation and feature engineering techniques
- Are familiar with statistical methodologies.
- Have good communication skills.
Benefits
- private healthcare & dental insurance
- generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme to further reduce carbon emissions
- extra festive time off
- excellent family-friendly benefits
- clear career paths
- transparent pay bands
- personal learning budgets
- regular learning days
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