Senior AI/ML engineer
Role details
Job location
Tech stack
Job description
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
Requirements
Do you have experience in Unity?, Do you have a Master's degree?, * 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, * 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)
Benefits & conditions
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