Senior AI/ML engineer in London

Flo is the world’s #1 health & fitness app on a mission to build a better future for female health. We are looking for an AI/ML Platform Engineer to join the AI Platform team. This team builds and maintains Flo’s shared platform for artificial intelligence, enabling every product team to use AI safely, efficiently, and at scale.

If you’re passionate about cutting‑edge generative AI technologies and driven by building robust ML infrastructure that delivers value to millions of users, we would love to hear from you. In this role, you will work at the intersection of machine learning engineering and MLOps, owning both the development and operationalization of AI/ML systems. Your responsibilities will span from fine‑tuning and optimising large language models to building and maintaining the infrastructure that enables rapid experimentation and reliable deployment at scale.

The AI Platform team acts as the central enabler of machine learning and AI initiatives across the organisation. Its mission is to reduce operational overhead and maximise ROI from ML use cases. The team builds and maintains critical infrastructure including LLM evaluation frameworks (AI Judges), model deployment pipelines, fine‑tuning infrastructure, user profiles store, experiment tracking systems, and monitoring frameworks.

By working closely with domain teams, the AI Platform team delivers scalable, high‑quality solutions that accelerate time‑to‑market while ensuring compliance and maintaining the highest standards of performance.

What you’ll be doing:

• Develop, fine‑tune, and optimise large language models for domain‑specific health applications, working with both proprietary and open‑source models (Gemini, GPT, Llama, etc).
• Design and maintain automated pipelines for model training, fine‑tuning, evaluation, and deployment across diverse AI workloads.
• Build and enhance LLM evaluation frameworks (AI Judges) for measuring model safety, medical accuracy, and performance.
• Implement CI/CD practices for ML/AI engineering workflows, including experiment tracking, model versioning, and automated testing.
• Orchestrate seamless deployment of models, AI agents, and inference endpoints with automated testing and rollback capabilities.
• Implement comprehensive monitoring for model performance, drift detection, AI safety metrics, and responsible AI compliance.
• Constantly improve technical capabilities by researching and implementing best practices in the rapidly evolving space of LLMs and generative AI.
• Work in a cross‑functional setup alongside other Flo Teams (Product, Security, Analytics, Marketing, Legal, etc).

Must have:

• 4+ years of professional experience in machine learning, with hands‑on experience building and deploying production‑grade AI/ML systems.
• Recent engineering experience with LLM infrastructure and tooling, including fine‑tuning (LoRA, SFT or other), prompt engineering, and model evaluation.
• Strong Python programming skills for efficient model development, experimentation, and deployment.
• Experience with modern ML infrastructure tools such as MLflow, experiment tracking systems, and model registries.
• Databricks (or similar tooling) platform experience with Unity Catalog, MLflow, and Databricks Machine Learning for end‑to‑end AI/ML workflows.
• Cloud platform expertise with one of the Hyperscalers (AWS, GCP, or Azure) including AI‑specific services.
• Understanding of the entire ML/LLM development lifecycle, including CI/CD, version control, testing, and agile methodologies.
• Ability to devise creative solutions to intricate technical challenges, including experience in systems design with the ability to architect and explain ML/LLM pipelines.
• Excellent communication skills and ability to collaborate with diverse teams.
• Commitment to responsible AI practices, including fairness, accountability, and transparency.

Nice to have:

• Experience with LLM fine‑tuning techniques including LoRA adapters, preference optimisation (RLHF/DPO), and model distillation.
• Containerisation and orchestration experience with Docker, Kubernetes, and ML‑specific operators.
• AI model serving experience with modern inference servers and API gateways for AI applications.
• Infrastructure as Code experience with Terraform, Ansible, or other IaC tools.
• Experience building and managing data pipelines using tools like Apache Spark.
• AI safety and governance experience with model evaluation, LLM judges, bias detection, and responsible AI practices.
• Familiarity with statistical fundamentals and running and evaluating experiments.
• Experience in the MedTech or HealthTech domain.
• Experience at a Tier‑1 product company or related experience working within a product organisation.

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.
• Flexible office + home working, up to 2 months a year working abroad.
• 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.