Senior AI/ML engineer

Overview

In this role, you will join Flo’s AI Platform to build and operate AI/ML systems used across product teams. You’ll fine-tune and optimize large language models and maintain scalable ML infrastructure, enabling safe, fast experimentation and deployment at scale. The work centers on medical-safe AI, evaluation frameworks, and robust pipelines that support the company’s privacy-first health ambitions. You’ll collaborate with cross-functional teams to accelerate time-to-market while maintaining high standards of performance and compliance. This is an opportunity to shape the next generation of AI in health at a market-leading, mission-driven company.

Pay / Benefits

• competitive salary
• annual reviews
• performance incentive scheme
• paid holiday, sick leave, female health leave
• enhanced parental leave
• 5-week sabbatical at 5-year anniversary

Responsibilities

• Develop, fine-tune, and optimize large language models for domain-specific health apps using proprietary and open-source models
• Design and maintain automated training, fine-tuning, evaluation, and deployment pipelines across AI workloads
• Enhance LLM evaluation frameworks (AI Judges) for safety, medical accuracy, and performance
• Implement CI/CD practices for ML/AI workflows, including experiment tracking and model versioning
• Orchestrate deployment of models, AI agents, and inference endpoints with testing and rollback
• Monitor model performance, drift, AI safety metrics, and responsible AI compliance
• Research and adopt best practices in LLM/generative AI to improve capabilities
• Collaborate with cross-functional teams (Product, Security, Analytics, Marketing, Legal)

Key requirements

• 4+ years of professional ML experience with production-grade AI/ML systems
• Recent experience with LLM infrastructure, fine-tuning, prompt engineering, and model evaluation
• Strong Python for model development and deployment
• Experience with ML tooling such as MLflow, experiment tracking, and model registries
• Databricks platform experience (Unity Catalog, MLflow, Databricks ML) for end-to-end workflows
• Cloud platform expertise with AWS, GCP, or Azure, including AI-specific services
• Understanding of the full ML/LLM lifecycle including CI/CD, version control, testing, and agile methods
• Ability to design ML/LLM pipelines and articulate architectural decisions
• Excellent communication and cross-team collaboration
• Commitment to responsible AI practices (fairness, accountability, transparency)

• collaboration
• creative problem solving
• clear communication
• LLM fine-tuning (LoRA, SFT or similar)
• prompt engineering
• model evaluation

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