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- Tasks: Design and deploy machine learning models for personalised health recommendations.
- Company: Healf, a digital-first wellbeing platform transforming health shopping.
- Benefits: Premium Wellhub membership, 50% off products, and a wellbeing-focused workspace.
- Why this job: Join a movement to redefine wellbeing with cutting-edge technology and impactful projects.
- Qualifications: 4-6 years in machine learning, experience with recommendation systems, and strong Python skills.
- Other info: Collaborative culture with opportunities for personal and professional growth.
The predicted salary is between 42000 - 84000 ÂŁ per year.
Build the Future of Wellbeing
Do Your Life’s Best Work
If modern wellbeing were redesigned from scratch, it wouldn’t live in a GP’s office or a cluttered supplement aisle. It would be digital-first, beautifully curated, and powered by data that actually helps you feel your best. That’s what we’re building at Healf. An ecommerce platform at the intersection of personalised health and curated wellbeing. We connect customers with the world’s most effective products across EAT, MOVE, MIND, and SLEEP, and we’re just getting started. We combine culture-shaping storytelling, cutting-edge health tech (like our new blood testing platform, Healf Zone), and a best-in-class product experience to help people build rituals that work. Backed by investors behind Soho House, Alo Yoga, Cult Beauty, and Innocent, we’re scaling fast, and redefining how the world shops and lives well.
About Us
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. Experience with LLMs, embedding models, and applied AI systems will be highly valuable as we evolve towards conversational and contextual recommendation systems.
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 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: Thehealthylivingstore
Contact Detail:
Thehealthylivingstore 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 potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommendations. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and algorithms. Practice explaining your past projects and how they relate to Healf’s mission. Confidence and clarity can make all the difference!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. 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 understand what you bring to the table!
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 Thehealthylivingstore
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, 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 Curiosity
Healf values relentless curiosity, so come prepared with questions about their products and the technology behind them. Demonstrating your interest in how data can drive wellbeing will show that you're aligned with their mission and culture.
✨Collaborate Like a Pro
Since this role involves working closely with Product and Data teams, be ready to share examples of how you've successfully collaborated across functions in the past. Highlight your ability to translate business goals into technical objectives, which is key for this position.
✨Experimentation Mindset
Talk about your experience with A/B testing and performance measurement. Healf is looking for someone who can continuously optimise model performance, so sharing specific examples of how you've approached experimentation will set you apart.
