Trainline on cord

Trainline

Machine Learning Engineering Manager

External position
London, UK
Hiring internally for Trainline?
Travel 路 Transport 路 Ticketing
The world鈥檚 leading independent rail and coach travel platform
Posted
3 days ago
Checked
cord regularly checks that external positions are still open
21 hours ago

Skills & Experience

Job roles: Machine Learning Engineer
Experience level: Senior, Lead, Leadership
Core skills considered: Machine Learning, Python, AWS, Data Pipelines
Other skills considered: A/B Testing, CI/CD, Data Modeling

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

We're looking for a Machine Learning Engineering Manager to lead a team of 7 ML engineers and data engineers within our Core Experience pillar, which covers Search, Supply and Commerce. Your team's work sits at the centre of how customers find, compare and buy their tickets. You'll be accountable for what your team ships and how it ships it: the quality of the systems, the pace of delivery and the growth of the people building them. You'll work alongside data scientists, software engineers and product managers. You'll stay close enough to the technical work to make good calls on architecture, trade-offs and risk.

In this role, you will... 馃殑


Responsibilities

  • Lead, coach and grow a team of ML and data engineers. That means setting clear expectations, giving regular feedback, managing performance and building an inclusive team where people do their best work
  • Hire for the team, shaping the roles we need and running a fair, rigorous interview process
  • Own delivery: plan and prioritise with your product partners across Search, Supply and Commerce, unblock the team, and ship ML and AI systems that move measurable customer and business outcomes
  • Set the technical direction for your team's systems, including architecture, build-versus-buy, and knowing when a simpler approach beats a more sophisticated one
  • Make sure the team builds well across the whole lifecycle: reliable data pipelines, high-quality features, rigorous offline and online evaluation (including A/B testing), reliable deployment, monitoring and ongoing maintenance
  • Lead the team in building production-grade agentic systems, using orchestration harnesses such as LangGraph to design multi-step workflows, tool use and human-in-the-loop controls
  • Make evaluation a first-class engineering discipline for LLM and agent work. That means curated eval sets, LLM-as-judge and human review, tracing, regression testing of prompts and agents, and online monitoring of quality, cost and latency
  • Set the guardrails for responsible use of AI, covering safety, privacy and clear fallbacks when an agent shouldn't act on its own
  • Raise the bar on engineering practice through code and design reviews, CI/CD, MLOps, observability and on-call
  • Build strong relationships with senior leaders and partner teams, explaining progress, trade-offs and impact in plain language
  • Contribute to our wider AI and ML community and help keep a culture of learning, curiosity and experimentation

We'd love to hear from you if you have... 馃攷


Requirements

  • Experience line-managing engineers, including hiring, performance management and career development
  • A strong background as an ML engineer, with a track record of taking models into production and keeping them healthy at scale
  • Enough grounding in data engineering (pipelines, data modelling and data quality) to lead data engineers as well as ML engineers
  • Solid Python and software engineering fundamentals, with enough hands-on depth to review code and designs credibly
  • Depth in at least one area such as ranking and recommendation, predictive modelling, optimisation or NLP, backed by a solid grasp of statistics, experimentation and feature engineering
  • Experience with modern ML infrastructure on a major cloud platform, ideally AWS, covering distributed data processing, orchestration, model management and infrastructure as code
  • Hands-on experience shipping agentic or LLM-based systems, including agent orchestration frameworks, tool use, RAG, and fine-tuning where it earns its place
  • A disciplined approach to evaluating LLM and agent systems, using tools such as Braintrust, and a clear view on how to know whether an agent is working well in production
  • Clear communication with technical and non-technical colleagues, and good judgement on priorities when there's more to do than people to do it
Machine Learning Engineering Manager at Trainline
Position posted 3 days ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech 路 Banking 路 Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: 拢70K - 拢110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK鈥檚 first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK鈥檚 first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We鈥檙e a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We鈥檙e a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day鈥檚 holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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