Engineering Lead II - Machine Learning Platform

Wise
London
2 days ago
Create job alert

Job Description

Enter: our Machine Learning Platform team!

For our customers, using Wise is as simple as sending money from A to B. Yet behind our app and website is a complex engine of currencies, routes, products and features, generating terabytes of data each day. The Data services offered by the Data Platform is at the core of systems that store, process and leverage this data, ultimately providing real time insights that serve as one of many drivers for business growth.

Your mission and role will be to lead the team building and maintaining a cost efficient and scalable machine learning platform, that is convenient to use and that provides a good engineering and data science experience. Your input will directly affect how Wise is making decisions and predictions on billions of events.

How we work

We operate with a belief in automation, programmatic implementation, and reusable design. We’re looking for people who can step back and think holistically about the ecosystem, but also follow through and help implement the design; drawing on the resources across the rest of the platform tribe.

As we grow, it is imperative to protect our customers’ money and navigate complex regulatory requirements world-wide. You will have a focus on running and maintaining the data services, making sure we have the right observability and service management elements in place, with an eye for high-availability, assessing and reducing engineering load and devising more effective ways for the team to look after its cloud-based platform.

We need to sustain this growth by continuously iterating on the services we run, with a focus on availability, security, and ease of use. We’re looking for an engineer with relevant experience who can understand and respond to complex requirements and deliver simple solutions to help our teams achieve our mission with speed and confidence. 

What does it take?

  1. You are a strong leader, experienced in problem-solving and guiding engineering teams through the complexities of project delivery using both agile and traditional methodologies.

  2. Comfortable taking ownership of vendor negotiations and explaining costs to the business

  3. Great communication skills and the ability to build consensus - you’re comfortable making a case for what you believe we should be doing

  4. Experience being a self-starter, self-motivated and collaborative

  5. Willingness to give and take regular feedback - regular feedback is part of our culture

What do you need?

We are fully aware that it is uncommon for a candidate to have all skills required and we fully support everyone in learning new skills with us. We value potential and enthusiasm as much as existing expertise.  So if you have some of those listed below and are eager to learn more we do want to hear from you!

  • You have a solid background in software engineering, ideally within the Python or Java ecosystems, upholding high coding standards and a thorough understanding of system design and engineering principles.

  • Understanding of test coverage best practices & the test pyramid concept, and you are well versed in writing effective, scalable and clean code

  • You have experience designing and implementing distributed and concurrent systems, knowing the tradeoffs between stateful/stateless and synchronous/asynchronous architectures

  • You have ability to take initiative while working collaboratively - identify problems, empathise with stakeholders and collaborators, create plans and implement solutions

  • You are a great communicator with the ability to clearly relay your plans back to the team, mentor junior engineers and seek out feedback for yourself

  • The customer is at the heart of everything you do and this empathy drives the decisions you make

Nice to haves:

  • Passionate about technology and its relationship with product and user experience

  • You are a security and privacy advocate, understanding concepts such as principle of least privilege, and are able to apply basic security principles at infrastructure and application level.

  • You have knowledge of cloud based ML solutions from GCP or AWS

  • Experience with streaming data processing frameworks such as Flink, Beam, Spark, Kafka Streams

  • Experience with Ansible, Terraform, GitHub Actions, Infrastructure as Code, AWS or other cloud ecosystems

  • Knowledge/interest in payment platforms, foreign exchange & complex systems architecture

  • Be a customer of Wise

What you get back:

  • The opportunity to create meaningful change for our customers and team

  • Loads of development opportunities

  • Work with a team of passionate Machine Learning Engineers who love improving the lives of our fellow Wisers

  • A fun work environment with social activities and events

And more… Check out our offer here.

Interested? Find out more:

What do we offer: 

We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in. 

Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you. 

And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.


Additional Information

For everyone, everywhere. We're people building money without borders  — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.

Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

Related Jobs

View all jobs

Senior Data Scientist II

Data Scientist II - QuantumBlack Labs

Machine Learning Engineering Lead

Machine Learning Engineering Lead

Machine Learning Engineering Lead

Machine Learning Engineering Lead

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.