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Staff Engineer, AI/ML

Checkout.com · London

Location
London
Employment
Full time
Level
Staff
Posted
2 months ago

About this role

Company Description

We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day.


We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers.

Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.

If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact.

With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech - and we’re just getting started.

There are a myriad of opportunities to use AI / ML as part of business processes in checkout, and we’re looking for an expert to help us make these a reality. Unlike many such roles, this is an opportunity to truly drive innovation at scale that matters.

We’re looking for a Staff Level AL / ML engineer to accelerate our adoption into the AI era; helping us set our AI vision and show us what is possible.

As part of the Data and AI platform team; you’ll get to pioneer on real world problems, bringing your knowledge of AI / ML, MLOps and LLMs to bear - collaborating cross team to make your vision a reality. You’ll be backed by our platform team, and have a wealth of experience to draw on, but we want someone who’ll blaze a trail; operating on the bleeding edge.

How you’ll make an impact:

  • Collaborate with teams to research, scope, and validate use cases for AI that drive business value and innovation.

  • Drive AI adoption by combining rigorous scientific evaluation with the operational maturity to champion high-value applications and confidently push back on unsuitable AI use cases.

  • Design, refine and build MLOps component of the data and AI platform, from Vector Databases through feature stored and model serving, all at the millisecond scale.

  • Implement CI/CD pipelines and ensure adherence to best practices for model deployment, security, and compliance with global regulations.

  • Work as part of our AI / ML guild; having a voice and being a driving force behind new approaches and use cases.

  • Continuously monitor and optimise system performance to ensure scalability, security, and operational efficiency.

What we’re looking for:

  • Proficiency in Python (and at least one other language a plus). Experience with key libraries such as PyTorch, Pandas, Hugging Face Transformers, or similar AI toolkits.

  • Working knowledge of common models, and their use cases and experience applying them to solve specific problems.

  • Solid engineering skills, including designing and implementing services / data models and features.

  • Expertise with cloud computing platforms (AWS, GCP, or Azure) and containerisation tools (e.g., Docker, Kubernetes).

  • Expertise with modern data platforms (e.g., BigQuery / Databricks) and data processing workflows (ETL, pipelines).

  • Excellent experience with cloud hosted AI platforms (Bedrock, Sagemaker, VertexAI)

  • Strong problem-solving abilities, with the capacity to learn quickly and adapt in a fast-paced environment.

  • Excellent communication and a drive to work effectively across diverse teams.

We also want to hear if you have:

  • Experience developing AI / ML applications, including fine-tuning models or creating prototypes.

  • Awareness of ethical considerations and emerging best practices in AI governance.

  • Track record of developing rapid prototypes, and bringing them to production with a focus on measurable ROI.

  • Familiarity with distributed systems and large-scale data processing.

  • Contributions to open-source projects or a strong GitHub portfolio.

  • Thought leadership, any articles or talks you’ve given?

  • High levels of technical curiosity and an eagerness to learn new platforms

Additional information:

  • Hybrid Working Model: All of our offices globally are onsite 3 times per week (Tuesday, Wednesday, and Friday). We’ve worked towards enabling teams to work collaboratively in the same space, while also being able to partner with colleagues globally. During your days at the office, we offer amazing snacks, breakfast, and lunch options in all of our locations.

Additional Information

Bring all of you to work

We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one.

Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands.

We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.

It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable.

Life at Checkout.com

We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.

Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us.

For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram

As published by Checkout.com. Applications are handled on their site.

One click, then it is written

Apply to Checkout.com with a resume written for this role.

Queue Staff Engineer, AI/ML and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Checkout.com’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • 25 sent a week, free
  • No card
  • Nothing sent until you say so

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Put this to work

Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board Checkout.com publishes. Refolk is not the employer and does not handle their hiring. Applications go to Checkout.com directly.