Machine Learning Engineering Manager

About the Role

Our machine learning teams own the complete delivery lifecycle from ideation to production. We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout [Employer hidden]. We are looking for a Machine Learning Engineering Manager to join our team help shape the future of train travel. You will be part of a highly innovative AI and ML platform working alongside engineers, scientists and product managers to tackle complex challenges by combining [Employer hidden]’s rich datasets with cutting edge algorithms. What unites our team is an expertise in the field, a love of what we do and the desire to create impactful solutions to support [Employer hidden]’s goals of encouraging sustainable travel. As a part of [Employer hidden] you will be joining an environment where learning and development is top priority. You will have the opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users.

What you'll do

• 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 [Employer hidden]’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

Who you are

• 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 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 of understanding of data extraction, data manipulation and feature engineering techniques
• Are familiar with statistical methodologies
• Have good communication skills

Desirable

• Experience with transport industry and/or geographical information systems (GIS)
• Experience with cloud infrastructure
• Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents)
• Experience with graph technology and/or algorithms

Our technology stack

• Python and associated ML/DS libraries (scikit-learn, numpy, LightlGBM, Pandas, LangChain/LangGraph, , TensorFlow, etc...)
• PySpark
• AWS cloud infrastructure: EMR, ECS, Athena, etc
• MLOps: Terraform, Docker, Airflow, MLFlow

Company Benefits

• Flexible working (60% min office attendance)
• Cycle to work scheme
• Discounted gym memberships through Wellhub
• Private Health and Dental Insurance
• Enhanced Pension (matched contributions)
• Income Protection
• Share Incentive Plan (buy one get one free)
• Learning budget
• Primary & Secondary Caregiver Leave
• Shared Parental Leave
• Enhanced sick pay
• Free Perkbox subscription
• Electric Vehicle Salary Sacrifice Scheme
• YellowNest - Subsidised Childcare Fees
• Work from Abroad

About [Employer hidden]

[Employer hidden] make it super easy to book transport tickets. Its app is intuitive and well designed and its even pioneering paperless travel, allowing users to store their tickets in the app. It's hyper-focused on customer experience and has a product culture of fast iteration to deliver great outcomes for customers. Its customers make 170,000 journeys a day and it sells 200 tickets a minute. It's continuing to innovate to stay ahead, using machine learning to predict price movements and integrating with Siri and Google Assistant so people can buy tickets simply by speaking to their phone.

Application Instructions: Apply