Machine Learning Engineer (recommendations)

London, ENG, GB, United Kingdom

Job Description

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 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.

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Job Detail

  • Job Id
    JD4140738
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Full Time
  • Job Location
    London, ENG, GB, United Kingdom
  • Education
    Not mentioned