Staff Product Engineer, AI in London

Staff Product Engineer, AI in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
United States Digital Space LLC

At a Glance

  • Tasks: Build cutting-edge AI products and collaborate with talented ML Scientists.
  • Company: Join a fast-growing AI company transforming customer experiences.
  • Benefits: Enjoy competitive salary, equity, flexible holidays, and comprehensive health insurance.
  • Other info: Hybrid work policy with a focus on collaboration and inclusivity.
  • Why this job: Make a real impact in AI while working in a dynamic, supportive environment.
  • Qualifications: 10+ years of product engineering experience; ML knowledge is a plus but not required.

The predicted salary is between 60000 - 80000 £ per year.

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support.

We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

If you are an experienced product engineer who takes an analytical approach to development and has some hands-on experience with ML systems, we'd love to hear from you!

What will I be doing?

  • Build the systems that power Fin's flagship AI products, usually working in our ML Python tech stack, but at times also across the product on our Rails app.
  • Work alongside our ML Scientists to bring proof-of-concept code to production; ensuring it’s robust and scalable for real-world use.
  • Partner with product teams outside of our group, to shape the best AI-powered product experience for our customers.
  • Contribute to all phases of software development including ideation, prototyping, implementation and testing.
  • Play an active role in the hiring, mentoring, and career development of other engineers.
  • Raise the bar for technical standards, performance, reliability, and operational excellence within the group and across Fin.

Profile we’re looking for

  • 10+ years of experience shipping high-quality products.
  • No ML experience required. We believe you can be highly effective immediately by bringing excellent software engineering skills, and learn ML as you work on the team.
  • You can demonstrate significant impact in the work that you have done.
  • You take pride in having strong technical fundamentals; you love learning and are willing to work hard to invest in your development.
  • Deep knowledge of a high-level programming language (for example, Ruby, Python, Javascript etc.) but it doesn’t need to be a language that we use here!
  • Strong willingness to fight for good outcomes.
  • Bias towards progress over perfection.
  • BSc in Computer Science, Maths or Statistics or related discipline.

Bonus skills & attributes

  • Previous experience in data analytics, or statistical role.

Benefits

  • Competitive salary and equity in a fast-growing start-up.
  • We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen.
  • Regular compensation reviews - we reward great work!
  • Pension scheme & match up to 4%.
  • Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents.
  • Open vacation policy and flexible holidays so you can take time off when you need it.
  • Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones.
  • If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too.
  • MacBooks are our standard, but we also offer Windows for certain roles when needed.

Policies

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.

Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

Staff Product Engineer, AI in London employer: United States Digital Space LLC

At Fin, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through regular compensation reviews, open vacation policies, and a supportive environment for learning and development in AI technologies. Located in a vibrant area, we provide competitive salaries, equity options, and comprehensive benefits, ensuring our team members feel valued and empowered to make a meaningful impact.

United States Digital Space LLC

Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Product Engineer, AI in 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 United States Digital Space LLC 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

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Explore Job Boards Specifically for Tech Roles

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We think you need these skills to ace Staff Product Engineer, AI in London

Machine Learning
Python
Software Engineering
Prototyping
Collaboration
Technical Fundamentals
Data Analytics

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 United States Digital Space LLC.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC 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 United States Digital Space LLC

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 United States Digital Space LLC 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.