At a Glance
- Tasks: Design and deploy machine learning models for personalised health recommendations.
- Company: Healf, a transformative ecommerce platform for wellbeing.
- Benefits: Premium Wellhub membership, exclusive discounts, and a wellbeing-focused workspace.
- Why this job: Join a movement to reshape health and wellness with cutting-edge technology.
- Qualifications: 4-6 years in machine learning, experience with recommendation systems, and strong coding skills.
- Other info: Collaborative culture with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
Healf was founded by two brothers - Max and Lestat - with a relentless drive to reshape health and wellness. Their journey has been fuelled by hard work, intensity, and a commitment to build something transformative. Like all of us, they’re here to make a lasting impact.
At Healf, we’re not just a company, we’re a movement. Founded by two brothers whose own wellbeing journeys inspired our mission to empower others, Healf is built on grit, determination, and a shared understanding of the power of wellbeing. Our culture is grounded in The Healf Standard—five principles that define how we work and win:
- We Work Harder Than Anyone Else: Building something that improves lives takes long hours, grit, and sacrifice, but we thrive on it. We all feel energised by what we’re building.
- Never Settle: We challenge the status quo and push ourselves to be better every day. We never settle for mediocrity or the idea that something can’t be done.
- Obsession Over Talent: Talent alone isn’t enough—relentless curiosity and a drive to grow set us apart.
- The Healf Lifestyle: We live what we preach—our personal commitment to wellbeing fuels our professional productivity.
- Stronger Together: Everyone owns their lane, but we run as a unit.
With Healf Zone on the horizon, we’re entering the next phase of our journey: closing the loop on health with personalised, preventative care that unlocks longevity and optimised wellbeing. This is your chance to help build something that’s not only extraordinary, but a first of its kind.
The Role
We’re looking for a Machine Learning Engineer – Recommendations to help build the foundation of Healf’s personalisation and intelligence platform. You’ll design, train, and deploy recommendation models that power dynamic merchandising, personalised discovery, and tailored health journeys across web, app, and beyond. This is a highly cross-functional role working closely with Product, Data, and Engineering to turn raw data into real-time insights and experiences. Over time, you’ll also contribute to developing predictive algorithms that help users make better health decisions — forming the intelligence layer of Healf’s long-term vision: a wellbeing platform powered by AI and data.
Where You’ll Make An Impact
- Build and evolve Healf’s recommendation engine, driving personalised product discovery and dynamic merchandising across web and app.
- Develop and deploy machine learning models that optimise product relevance, content ranking, and user engagement.
- Partner with Product and Data teams to define and capture the signals that power our personalisation logic.
- Contribute to the development of predictive algorithms that leverage data from Healf Zone, Helix, and user behaviour to anticipate customer needs.
- Collaborate with Engineering to integrate ML systems into production pipelines and ensure scalable performance.
- Experiment with LLM-based retrieval and recommendation architectures.
- Continuously measure, evaluate, and optimise model performance through experimentation and A/B testing.
- Help shape the roadmap for Healf’s broader wellbeing intelligence platform — connecting data, health insights, and user intent.
- Champion data quality, ethics, and compliance in all model design and deployment processes.
What You’ll Bring
- 4–6 years of experience as a Machine Learning Engineer or Data Scientist, ideally within eCommerce, consumer tech, or recommendation systems.
- Strong background in building and deploying ML models using Python, PyTorch, TensorFlow, or similar frameworks.
- Proven experience with recommendation engines, ranking algorithms, or personalisation pipelines.
- Familiarity with LLMs, embeddings, and NLP techniques for recommendation and content matching.
- Proficient in SQL and data manipulation tools; experience working with modern data stacks (e.g., dbt, Snowflake, BigQuery).
- Solid understanding of MLOps practices — model versioning, CI/CD, and production monitoring.
- Comfortable working across product and engineering teams to translate business goals into model objectives.
- Experience with experimentation, A/B testing, and performance measurement.
- Curious, self-directed, and excited to build the intelligence layer behind the future of personalised wellbeing.
Why Join Healf
- Do your life’s best work: Build something that matters, with a team that moves fast and aims high.
- Surround yourself with A+ talent: You’ll work with high-performers who care deeply and raise the standard every day.
- Be a builder: This isn’t a cog-in-the-machine role. You’ll help shape our voice, culture, and growth.
- Wellbeing is the lifestyle: From office yoga to Healf Zone insights, everything we do is rooted in our pillars: EAT MOVE MIND SLEEP.
- Premium Wellhub Membership: Unlimited entry to 1000's of gym, yoga, & fitness studios.
- Exclusive Healf Perks: 50% off all Healf products plus discounted Healf Zone blood testing.
- Nest Pension: Secure your future with our pension contributions.
- Wellbeing-Focused Workspace: Incredible Hammersmith office with great natural lighting.
- Team Connection: Annual company-wide retreat to recharge and bond.
Machine Learning Engineer (Recommendations) in London employer: Healf
Contact Detail:
Healf Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Recommendations) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with Healf employees on LinkedIn. A personal introduction can make all the difference when you're applying for that Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommendations or personalisation. This will give you an edge and demonstrate your passion for the field.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and understanding Healf's mission. Be ready to discuss how your experience aligns with their goals of building a transformative wellbeing platform.
✨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 the Healf movement.
We think you need these skills to ace Machine Learning Engineer (Recommendations) in London
Some tips for your application 🫡
Show Your Passion: When you're writing your application, let your enthusiasm for wellbeing and technology shine through. We want to see how your personal journey aligns with our mission at Healf. Make it clear why you’re excited about the role and how you can contribute to our vision.
Tailor Your Experience: Don’t just send a generic CV! Highlight your relevant experience in machine learning and recommendation systems. Use specific examples that demonstrate your skills and how they relate to what we’re building at Healf. We love seeing how your background fits into our goals.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and fluff. Make sure your key achievements and skills are easy to spot. This helps us quickly see how you can make an impact on our team.
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 ensures you’re considered for the role. Plus, it shows you’re serious about joining our movement at Healf!
How to prepare for a job interview at Healf
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially around recommendation systems. Be ready to discuss your experience with Python, PyTorch, and TensorFlow, as well as any projects you've worked on that relate to personalisation and dynamic merchandising.
✨Show Your Passion for Wellbeing
Healf is all about transforming health and wellness. Share your personal journey or interest in wellbeing and how it aligns with the company's mission. This will show that you're not just a techie but someone who genuinely cares about making an impact.
✨Prepare for Collaboration Questions
Since this role involves working closely with Product, Data, and Engineering teams, be prepared to discuss how you've successfully collaborated in the past. Think of examples where you translated business goals into technical solutions and how you handled any challenges.
✨Ask Insightful Questions
At the end of the interview, have some thoughtful questions ready. Ask about Healf's vision for the future of their recommendation engine or how they measure success in their ML models. This shows your genuine interest in the role and the company.