Lead Machine Learning Scientist (Customer Operations)

• The challenges are significant: we aim to transform customer service by reducing the time and effort required to resolve issues, enhancing customer confidence and satisfaction. As part of Operations, you’ll be at the forefront of our mission to provide unparalleled customer support experiences
• Your role will be pivotal in leveraging state-of-the-art machine learning techniques (including LLMs and autonomous agents) to understand customer problems. You will lead the development of an effective human-in-the-loop system that augments automation with the efforts of our support workforce (who we call COps)
• This allows us to more expediently and efficiently predict, identify, disambiguate, and route customer problems at scale to support a rapidly expanding company with global ambitions across multiple geographies
• You’ll be working closely with a team of ML engineers in Operations, embedded in product squads alongside data scientists, backend, mobile and web engineers, product managers, user researchers, designers, and operations specialists
• As a technical individual contributor, you’ll be providing technical leadership and shipping highly impactful ML-based solutions. You’ll be embedded in a cross-functional product squad, working closely with product managers, data scientists, backend engineers, and designers in an agile environment. You’ll also be a technical leader within the wider Machine Learning discipline, helping to steer technical work and drive up standards
• Working with stakeholders across the organisation to identify and scope out the most impactful opportunities to transform Customer Operations with Machine Learning
• Leading the design and development of advanced Machine Learning models, exploring how LLMs, RAG, and sequence-based architectures can drive improvements in query resolution and routing
• Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others
• Steering ongoing technical strategy, working closely with our MLOps team and backend engineers to enable rapid iteration of models and optimisations of the full ML model lifecycle

Benefits

• Yearly Salary Review + Proactive pay increases to reflect growing responsibilities + Share options
• Flexible working hours
• Work From Home Opportunities + we’ll pay for any equipment you need to do your job
• 24 days holiday a year, plus bank holidays
• Employee Assistance Programme
• Paid sick leave for both physical & mental health + Health insurance via AXA or Vitality + Additional health insurance through Medicash
• Learning budget of £1,000 a year
• Aviva Pension Scheme + 4% Employer Contribution
• Paid maternity, paternity, adoption or shared parental leave (after 13 weeks of employment)
• 52 weeks of primary caregiver leave (6 months at 100% pay, 13 weeks at Statutory Maternity Pay, 13 weeks unpaid)
• 3 months of secondary caregiver leave at 100% pay
• Unum Life Insurance
• Access to fertility and family-forming health benefits via Fertifa
• Abellio Season Travel Tickets + Cycle-to-Work Scheme- You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact
• You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
• You have extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices
• You want to be involved in building a product that you (and the people you know) use every day
• You have a multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
• You’re excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain
• You’re comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity
• You have a product mindset: you care about customer outcomes and you want to make data-informed decisions
• You’re adaptable, curious and enjoy learning new technologies and ideas
• You’re impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production
• Commercial experience writing critical production code and working with microservices
• Experience working with customer operations, capacity planning, forecasting, or in regulated institutions- Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions!
• 30 minute recruiter call
• 45 minute call with hiring manager
• 60 minute ML Modelling interview
• 60 minute Product & ML interview
• 60 minute behavioural interview
• Our average process takes around 3-4 weeks but we will always work around your availability
• You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on [email protected]
• Please also use that email to let us know if there’s anything we can do to make your application process easier for you, because of disability, neurodiversity or any other personal reason