- Senior
- Oficina en London
About Marshmallow
We exist to make migration easy.
A systemic problem of this magnitude requires a team of curious thinkers who relentlessly pursue solutions. Those who constantly challenge the why, dismantle assumptions, and always take action to build a better way.
A Marshmallow career is built on a cycle of continuous growth, with learning at its core. You will be challenged to raise the bar on your capabilities and supported with the right tools and guidance to do so. This ensures you can deliver impactful work and drive change.
If life at Marshmallow sounds like it could be for you, explore our Culture Handbook to find out more.
Move our mission, and your career, forward.
Data holds the secret code that unlocks the path ahead in our mission. That’s why data teams at Marshmallow are crucial in helping us to create technological solutions that make migration easy for hundreds of millions of global relocators every year.
Insightful. Strategic. Rigorous. A true team-player. Always ready to improve. We look for talent who’ll use their technical brilliance to build credibility across the business and make real commercial and world impact with every choice.
That’s why we provide a supportive environment full of trust and autonomy. So you can take ownership of high-leverage work, in a top functioning team that’s always moving forward.
The Data Science Team
Our central Data Science & AI team owns the end‑to‑end lifecycle of every model at Marshmallow, from experimentation to production. As an insurer‑fintech, serving hundreds of thousands of customers, reliability and speed are critical - our models quote prices, detect fraud and power next‑gen GenAI experiences in real time.
You will lead the ML Ops function within the team, line‑managing two ML Ops Engineers and reporting to the Director of Data Science & AI. Day‑to‑day you will partner with pricing and central data scientists, platform engineers and external vendors to ensure our models ship quickly, safely and at scale.
What you’ll be doing
Crafting and owning a multi‑year ML Ops roadmap that unlocks <24 h model iteration cycles and 99.9 %+ production uptime.
Scanning the horizon for emerging ML and GenAI technologies, and translating insights into practical pilots that keep Marshmallow at the forefront of innovation.
Setting and iterating the company‑wide MLOps & LLMOps strategy, covering classical ML and emerging generative‑AI workloads.
Hiring, coaching and inspiring a high‑performing ML Ops Engineering team with a culture of ownership and excellence.
Mentoring and developing the ML Ops Engineers, expanding the team as we grow and setting technical standards while promoting best practice across Data Science and Engineering.
Acting as the go‑to person for ML Ops questions from senior stakeholders and championing robust ML deployment across the business.
Making build‑versus‑buy decisions, evaluating new vendors and tooling, and negotiating contracts where relevant.
Championing a “You build it, you run it” culture so every data scientist can safely own their models in production.
Overseeing multiple deployment pipelines on AWS SageMaker (real‑time and batch inference) and integrating them with TeamCity for automated CI/CD.
Managing the relationship with Tecton as our feature platform vendor, advising Data Science teams on its use for training and inference, and overseeing related infrastructure cost and operation
Who you are
You are a strategic engineering leader who blends long‑term thinking with hands‑on delivery. You can articulate a compelling 3 to 5-year vision for ML Ops at a scaling fintech, then translate that into an actionable roadmap. You thrive in fast‑growing environments, where ownership is key and ambiguity is the norm. You continually scan the horizon for emerging ML and GenAI technologies and rapidly assess how they should reshape our tool‑chain and operating model. You have a track record of defining and owning ML Ops strategy, then landing it successfully to unlock measurable commercial value. You build high‑performing teams through clear direction, coaching and a strong engineering culture, and you hold a high bar for reliability, observability and developer experience.
What we're looking for from you
Experiences that are essential
End-to-end ownership of ML platforms servicing real-time, customer-facing products in regulated industries (finance, insurance, etc.).
Demonstrable success in hiring, developing and retaining high‑performing engineering teams, with evidence of managing, mentoring or leading.
Proven ownership of an ML Ops or ML platform roadmap that delivered clear business impact.
Production experience with the AWS ecosystem, especially SageMaker for training and hosting.
Strong Python skills and the ability to work and integrate with Java backend teams.
Hands‑on delivery of CI/CD for ML (e.g. TeamCity, Jenkins, GitHub Actions).
Infrastructure‑as‑code with Terraform (or similar) and containerisation with Docker.
Designing monitoring solutions that detect performance, drift and data‑quality issues in production.
Leading or mentoring engineers, and influencing cross‑functional stakeholders.
Experiences that will help you
Working with feature stores such as Tecton.
Implementing or integrating model‑monitoring platforms like Arize.
Deploying or operating LLM‑based applications at scale.
Negotiating with vendors and managing third‑party contracts.
Familiarity with Kubernetes or serverless architectures on AWS.
An understanding of FCA compliance considerations for ML services.
Comfortable with vector DBS, embedding management and model lifecycle tooling
Experience with model parallelism, distributed training
Perks of the job
Flexi-office working – Spend 2-3 days a week with your team in our new collaborative London office. The rest is up to you! 🏠
Competitive bonus scheme - designed to reward and recognise high performance 🌟
Flexible benefits budget - £50 per month to spend on a Ben Mastercard, meaning you get your own benefits budget to spend on things you want. Whether that’s subscriptions, night classes (puppy yoga, anyone?), the big shop or a forest of houseplants. Pretty much anything goes 💰
Sabbatical Leave - Get a 4-week fully paid sabbatical after being with us for 4 years 🏝️
Work From Anywhere - 4 weeks work from anywhere to use, with no need to come to the office 🛫
Mental wellbeing support – Access therapy and mental health sessions through Oliva 💚
Learning and development – Personal budgets for books and training courses to help you grow in your role. Plus 2 days a year - on us! - to further your skillset 🤓
Private health care - Enjoy all the benefits Vitality has to offer, including reduced gym memberships and discounts on smartwatches 🏥
Medical cash plan - To help you with the costs of dental, optical and physio (plus more!)
Tech scheme - Get the latest tech for less 🖥
Plus all the rest; 33 days holiday, pension, cycle to work scheme, monthly team socials and company-wide socials every month!
Our process
We break it up into a few stages:
Initial call with our Talent Acquisition Partner - 30 mins
A past experience interview where you will discuss your journey so far and ways of working with Paul, our Director of Data Science & AI - 60 mins
A technical interview with one of our Principal Data Scientists + Sr. ML Ops Engineers - 60 mins
A culture interview with a bar raiser to see if your work style fits our processes and values (and vice versa!) - 60 mins
Background checks
To meet our regulatory obligations as an FCA-authorised financial services company, we need to do some background checks on all new hires. That means carrying out a DBS check and making sure you don't have any live criminal proceedings. Feel free to ask our Talent Acquisition team if you have any questions about this!
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Everyone belongs at Marshmallow
At Marshmallow, we want to hire people from all walks of life with the passion and skills needed to help us achieve our company mission. To do that, we're committed to hiring without judgement, prejudice or bias.
We encourage everyone to apply for our open roles. Gender identity, race, ethnicity, sexual orientation, age or background does not affect how we process job applications.
We're working hard to build an inclusive culture that empowers our people to do their best work, have fun and feel that they belong.
Recruitment privacy policy
We take privacy seriously here at Marshmallow. Our Recruitment privacy notice explains how we process and handle your personal data. To find out more please view it here.
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