At a Glance
- Tasks: Lead the development of innovative machine learning products and mentor fellow engineers.
- Company: Join Fin, a fast-growing AI company transforming customer experiences.
- Benefits: Enjoy competitive salary, equity, flexible holidays, and comprehensive health insurance.
- Other info: Hybrid working policy with a focus on diversity and inclusion.
- Why this job: Make a real impact with cutting-edge ML technology in a collaborative environment.
- Qualifications: 5-8 years of applied ML experience and strong programming skills required.
The predicted salary is between 70000 - 90000 € 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.
Intercom’s Machine Learning team 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 ML product 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.
What will I be doing?
- Play an active role in hiring, mentoring and career development of other engineers
- Raise the bar for technical standards, performance, reliability, and operational excellence
- Identify areas where ML can create value for our customers
- Identify the right ML framing of product problems - Working with teammates and Product and Design stakeholders
- Conduct exploratory data analysis and research - Deeply understand the problem area
- Research and identify the right algorithms and tools - Being pragmatic, but innovating right to the cutting-edge when needed
- Perform offline evaluation to gather evidence an algorithm will work
- Work with engineers to bring prototypes to production
- Plan, measure & socialise learnings to inform iteration
- Partner deeply with the rest of team, and others, to build excellent ML products
What skills might I need?
- 5-8 years applied ML experience
- Previous background in a senior/staff role (data science, software development or academic)
- Significant, demonstrated impact that your work has had on the product and/or the teams
- Strong programming skills
- Experience as the primary technical leader for a team
- Strong communication skills, both within engineering teams and across disciplines
- Comfort with ambiguity
- Typically have advanced education in ML or related field (e.g. MSc)
- Scientific thinking skills
Bonus skills & attributes
- Track record shipping ML products
- PhD or other experience in a research environment
- Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering
- Strong stats or math background
- Visualization, data skills, SQL, matplotlib, etc.
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!
- 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’re happy to get you whatever equipment helps you get your job done
- Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organisation. We're committed to an inclusive and diverse Intercom! We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
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 Machine Learning Scientist in London employer: Fin
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, mentorship opportunities, and access to cutting-edge AI tools, all within a supportive environment that values diversity and inclusivity. Located in a vibrant area, our hybrid working policy ensures flexibility while maintaining strong team connections, making Fin an ideal place for those looking to make a meaningful impact in the field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Machine Learning Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Fin. A personal introduction can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your machine learning expertise. Bring it up during conversations or interviews to demonstrate your hands-on experience and passion for the field.
✨Tip Number 3
Be ready to chat about real-world applications of ML. Fin is all about delivering value to customers, so think of examples where you've used ML to solve problems or improve processes. This will show you're aligned with their mission.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Fin team.
We think you need these skills to ace Staff Machine Learning Scientist in London
Some tips for your application 🫡
Show Your Passion for ML:When you're writing your application, let your enthusiasm for machine learning shine through! We want to see how you've applied your skills in real-world scenarios and the impact you've made. Share specific examples that highlight your experience and passion.
Tailor Your Application:Make sure to customise your application to fit the role of Staff Machine Learning Scientist. Highlight relevant experiences and skills that align with our mission at Fin. This shows us that you understand what we're about and how you can contribute.
Be Clear and Concise:We appreciate clarity! Keep your application straightforward and to the point. Use bullet points where necessary to make it easy for us to read through your qualifications and experiences. Remember, less is often more!
Apply Through Our Website:Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Fin
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially the algorithms and tools mentioned in the job description. Be ready to discuss your past projects and how you've applied ML techniques to solve real-world problems.
✨Show Your Team Spirit
Since this role involves mentoring and collaborating with others, be prepared to talk about your experience working in teams. Share examples of how you've led projects or helped colleagues grow, as this will show you're a great fit for their collaborative culture.
✨Prepare for Technical Questions
Expect some technical questions that test your programming skills and understanding of ML concepts. Practise coding challenges and be ready to explain your thought process clearly, as communication is key in this role.
✨Understand Their Product
Familiarise yourself with Fin's AI Customer Agent and how it enhances customer experiences. Being able to discuss how your skills can contribute to their mission will demonstrate your genuine interest in the company and its goals.