Job Opportunities API

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 Software Engineer with deep expertise in AI/ML infrastructure to join our AI Platform team and help build the GenAI platform that powers every AI feature at Flo. You will bridge core infrastructure, data engineering, and LLM development to deliver production-grade medical safety judges, fine-tuning pipelines, evaluation frameworks, and real-time personalisation. The team operates 60+ LLM-based evaluation judges, develops proprietary fine-tuned health models, and maintains active partnerships with Databricks, Google, OpenAI, Anthropic, and AWS. What you’ll do LLM Judge Ecosystem: build and scale Judge-as-a-Service, prompt registries, calibration pipelines, and evaluation orchestration using MLflow 3.x Fine-Tuning and Serving: develop LoRA/SFT/preference optimisation pipelines for health-domain models (Llama, Gemma, MedGemma) and manage model serving at scale on Databricks Data and Evaluation Pipelines: build synthetic Q&A generation, golden test sets, reward function engineering, and Delta table schemas in Unity Catalog for reliable, reproducible evaluation data Infrastructure: maintain Terraform-managed AWS infrastructure (EKS, S3, IAM), Databricks AI Gateway, and CI/CD pipelines (GitHub Actions) with evaluation gates and progressive rollout Cross-Functional Impact: collaborate with Product, Security, Analytics, and Medical teams, develop internal SDKs and APIs consumed by 5+ teams, and engage directly with technology partners on pre-release capabilities Experience and skills Must have: Engineering maturity: 7+ years of software engineering, 4+ years focused on ML/AI platforms LLM experience: recent hands-on work with at least one of: fine-tuning, prompt engineering, LLM evaluation, or model serving Technical stack: strong Python across production services and data pipelines, data engineering fundamentals (Spark, Delta tables, Parquet) Platform and infrastructure: Databricks (MLflow, Unity Catalog, Model Serving), AWS (EKS/Kubernetes, IAM), Terraform, GitHub Actions Cross-domain flexibility: comfort working across ML, data engineering, and infrastructure. You don’t need to be expert in all three, but you contribute wherever the team needs it Nice to have: LLM evaluation frameworks (judges, graders, calibration methodology) or fine-tuning techniques (LoRA, RLHF/DPO, model distillation) ML data engineering: synthetic data generation, evaluation dataset design, annotation pipelines Healthcare, regulated industry, or safety-critical AI systems experience Prompt optimisation frameworks (DSPy or similar), feature stores (Tecton) #LI-KP1 #LI-Hybrid  Annual Salary Range (ranges may vary based on skills and experience) £120,000 — £150,000 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