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Flo Health

Senior AI/ML engineer

Flo Health is hiring a Senior AI/ML engineer in London, United Kingdom. It pays £120k-£180k a year and Level rates it ; you can apply on Flo Health.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions OpenAI, Anthropic and Llama among its tools and skills.
  • Level classes it as a senior role.
  • Flo Health has 32 other open roles on Level.

AI in this role

openaianthropicllamadspydatabricks
prompt-engineeringfine-tuningai-evaluation

500M+ downloads. 80M+ monthly users. A decade of building – and we’re still accelerating.

Flo is the world’s #1 health & fitness app worldwide on a mission to build a better future for female health. Backed by a $200M investment led by General Atlantic, we became the first product of our kind to reach a $1B valuation in 2024 – and we’re not slowing down.

With 7M paid subscribers and the highest-rated experience in the App Store’s health category, we’ve spent 10 years earning trust at scale. Now, we’re building the next generation of digital health – AI-powered, privacy-first, clinically backed – to help our users know their body better.

The job

We are looking for a Senior AI Engineer with strong LLM and product engineering experience to join our AI Platform team and help ship the AI-driven features across our app — including personalized in-app content recommendations, conversational AI-powered insights, and AI-generated mobile push notifications. You will focus on the product-facing behavior of our GenAI features (relevance, quality, latency, and safety), using the platform’s judges, fine-tuning pipelines, and evaluation tools, and contributing to infrastructure work (Databricks, AWS, Terraform) as initiatives require it.

What you’ll do

  • Feature development: build and ship LLM-powered product features, including AI-generated mobile push notifications, personalized in-app content recommendations and custom user journeys, and conversational AI-powered insights — including structured output such as charts and widgets
  • Latency and UX: reduce perceived and actual response latency through streaming, pregeneration, and inference-time tradeoffs, working closely with product and design on how AI output is experienced by users
  • Prompt and model behavior: iterate on prompt design and calibration, use fine-tuned health-domain models (Llama, Gemma, MedGemma) where relevant, and work with the Judge-as-a-Service ecosystem to keep outputs safe and high quality
  • Experimentation: help enable A/B testing for model and prompt changes, using evaluation gates to ship safely and measure impact
  • Data and evaluation: contribute to synthetic Q&A generation, golden test sets, and evaluation dataset design that supports the features you’re building
  • Infrastructure: contribute to Databricks, AWS (EKS), Terraform, or CI/CD work as initiatives require it
  • Cross-functional impact: collaborate with Product, Security, Analytics, and Medical teams, and engage with technology partners (Databricks, Google, OpenAI, Anthropic, AWS) on pre-release capabilities relevant to your features

Experience and skills

Must have:

  • 7+ years of software engineering, with recent hands-on experience building product features backed by LLMs
  • experience with at least one of: prompt engineering, LLM evaluation, fine-tuning, or model serving
  • strong Python, and comfort working with APIs/SDKs that wrap LLM calls, prompt templates, and structured outputs
  • product sensibility: a track record of shipping user-facing features, with attention to latency, tone, and quality of AI output as experienced by end users
  • comfort picking up new infrastructure tools (Databricks, AWS, Terraform, GitHub Actions) as needed — deep prior expertise not required

Nice to have:

  • LLM evaluation frameworks (judges, graders, calibration methodology) or fine-tuning techniques (LoRA, RLHF/DPO, model distillation)
  • prompt optimisation frameworks (DSPy or similar)
  • feature stores or personalization/ranking experience (relevant to in-app content recommendation work)
  • healthcare, regulated-industry, or safety-critical AI systems experience
  • data engineering fundamentals (Spark, Delta tables, Parquet)

#LI-KP1 #LI-Hybrid 

Annual Salary Range (ranges may vary based on skills and experience)£120,000—£180,000 GBP

How we work

We’re a mission-led, product-driven team. We move fast, stay focused and take ownership – from brief to build to impact. Debate is encouraged. Decisions are shared. We care about craft, ship with purpose, and always raise the bar.

You’ll be working with people who take their work seriously, not themselves. It takes commitment, resilience, and the drive to keep going when things get tough. Because better health outcomes are worth it. 

What you'll get

We support impact with meaningful reward. Here’s what that looks like:

  • Competitive salary and annual reviews
  • Opportunity to participate in Flo’s performance incentive scheme
  • Paid holiday, sick leave, and female health leave
  • Enhanced parental leave and pay for maternity, paternity, same-sex and adoptive parents
  • Accelerated professional growth through world-changing work and learning support
  • In-person collaboration and work in a hybrid model, with 3 days per week spent in the office
  • 5-week fully paid sabbatical at 5-year Floversary
  • Flo Premium for friends & family, plus more health, pension and wellbeing perks

Diversity, equity and inclusion

Our strength is in our differences. At Flo, hiring is based on merit, skill and what you bring to the role – nothing else. We’re proud to be an equal opportunity employer, and we welcome applicants from all backgrounds, communities and identities. Read our privacy notice for job applicants.

How we rate this

Senior AI/ML engineer at Flo Health rates 92 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringFine-tuningAI EvaluationOpenAIAnthropicLlamaDSPyDatabricks

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$200k

Use the typical machine learning engineer figure as a reference when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. How do you decide that one model's output is better than another's for a given task?
  4. What's a project where you used OpenAI hands-on?
  5. Walk me through how you've used Anthropic in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, Fine-tuning, AI Evaluation, OpenAI, and Anthropic. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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