At a Glance
- Tasks: Drive AI innovation and collaborate on impactful projects in a fast-paced environment.
- Company: Join Checkout.com, a leading fintech powering global digital experiences.
- Benefits: Enjoy competitive pay, hybrid work, and opportunities for personal growth.
- Other info: Flexible working model with a vibrant office culture and supportive team.
- Why this job: Be at the forefront of AI/ML technology and make a real difference.
- Qualifications: Proficiency in Python and experience with AI libraries and cloud platforms.
The predicted salary is between 80000 - 100000 £ per year.
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. 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 AI / 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.
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.
Staff AI/ML Engineer Software engineering London employer: Checkout
Checkout.com is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for professionals looking to make a significant impact in the financial technology sector. With a strong focus on employee growth and development, team members are encouraged to expand their skills and take on new challenges, all while enjoying the vibrant atmosphere of London. The company's commitment to regulatory excellence and strategic expansion offers unique opportunities for those passionate about shaping the future of global finance.
StudySmarter Expert Advice🤫
We think this is how you could land Staff AI/ML Engineer Software engineering London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Checkout or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Checkout.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Checkout.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Checkout that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Staff AI/ML Engineer Software engineering London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Checkout.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Checkout and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Checkout
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Checkout uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.