At a Glance
- Tasks: Develop cutting-edge ML models to improve health outcomes for over 250,000 users.
- Company: Join a mission-driven team at a leading HealthTech company.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with ambitious goals and a focus on learning.
- Why this job: Make a real impact in healthcare while working with top researchers and innovative technologies.
- Qualifications: Experience in ML model development and a passion for health technology.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- You’ve trained ML models that made it into production and helped thousands of people.
- You’ve led self-directed R&D projects and know how to navigate and spend time effectively in new and uncertain domains.
- You are excited to find ways to get 80% of the benefit from 20% of the effort, to push our understanding and our product forward at pace.
- You thrive in small mission-driven teams taking smart bets and learning as they go.
- You’ve previously worked in HealthTech or have experience with biometrics or high-frequency time series data.
- You invest time to understand the products you work on and their users, and are a valued voice in product discussions and ideation.
- You’re motivated to use your skills to help the more than 250,000 people using Visible to manage complex chronic illnesses.
- You use Claude Code or Codex (or similar) regularly and know how to delegate effectively to AI agents.
- You’re proactive and motivated to build a product you can be proud of: when you see how we could make something better, you make it happen.
- You form views based on evidence and change them when the evidence changes, always in service of our members and our business.
What the job involves
- You’ll develop production-grade machine learning models in novel and emerging domains (e.g. predicting symptom flare-ups, treatment effectiveness, diagnosis assistance using extensive time-series datasets).
- You’ll perform exploratory data analysis on both product and health data, and occasionally assist with product experiments (mostly A/B tests, some quasi-experimental).
- You’ll report to Paul, our Data Science Lead, in a small, low-ego team of 11: three engineers, one QA (we're hiring a second), three designers, two data scientists, a behavioural scientist, and a PM.
- You’ll support collaborations with researchers at top institutions (Imperial College London, Mount Sinai, Oxford, Yale) to inform robust, scientifically validated model development.
- You’ll work with our flexible tech stack: GCP, BigQuery, Python, Postgres, and our time series database InfluxDB.
Applied Machine Learning Engineer in London employer: Visible
At Visible, we pride ourselves on being an exceptional employer, particularly for those passionate about leveraging machine learning to make a real difference in health technology. Our collaborative and mission-driven work culture fosters innovation and personal growth, with opportunities to engage in cutting-edge research alongside leading institutions. Located in a dynamic environment, we offer flexible working arrangements and a supportive team atmosphere that empowers you to thrive while positively impacting the lives of over 250,000 users managing chronic illnesses.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the HealthTech space, especially those who work with machine learning. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that made it into production. Share your insights on how you tackled challenges and what impact your work had—this will make you stand out in interviews.
✨Tip Number 3
Prepare for the unexpected! In interviews, be ready to discuss how you approach R&D projects and navigate uncertainty. Think of examples where you’ve thrived in small teams and taken smart risks—this is what we love to see!
✨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 being part of our mission-driven team at StudySmarter.
We think you need these skills to ace Applied Machine Learning Engineer in London
Some tips for your application 🫡
Show Off Your Experience:Make sure to highlight any ML models you've trained that have made it into production. We want to see how your work has positively impacted users, especially in HealthTech or with time series data.
Be Proactive and Passionate:Let us know about your self-directed R&D projects and how you tackle new challenges. We love candidates who are excited to push boundaries and make things better for our users!
Understand Our Product:Take some time to understand what we do at StudySmarter and how our products help people manage chronic illnesses. Your insights on our product and its users will be invaluable in the application process.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and get to know you better. Plus, it shows you're keen to join our mission-driven team!
How to prepare for a job interview at Visible
✨Know Your ML Models Inside Out
Make sure you can discuss the machine learning models you've trained in detail. Be ready to explain how they were developed, the challenges you faced, and the impact they had once deployed. This shows your hands-on experience and understanding of production-grade models.
✨Showcase Your R&D Experience
Prepare examples of self-directed R&D projects you've led. Highlight how you navigated uncertainty and what strategies you used to achieve results. This will demonstrate your ability to thrive in dynamic environments and contribute to innovative solutions.
✨Emphasise Your User-Centric Approach
Be prepared to discuss how you invest time in understanding the products you work on and their users. Share specific instances where your insights influenced product discussions or ideation, showcasing your value as a team member focused on user needs.
✨Familiarity with Tech Stack is Key
Brush up on the technologies mentioned in the job description, like GCP, BigQuery, and Python. If you have experience with time series data or tools like Claude Code or Codex, be ready to talk about how you've used them effectively in past projects.
