MLOps engineer

500M+ downloads. 77M+ 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 6M paid subscribers and the highest-rated experience in the App Store’s health category, we’ve spent 10 years earning trust , we’re building the next generation of digital health – AI-powered, privacy-first, clinically backed – to help our users know their body better.

In this role, you will own the end-to-end AI/ML pipeline, including CI/CD processes for ML and AI engineering workflows. Your responsibilities will encompass managing code, versioning datasets, foundation and fine-tuned models, AI agents, and production endpoints. This will enable ML Engineers to collaborate effectively, experiment efficiently, and scale rapidly across both traditional ML workloads and modern AI applications.

The AI Platform team acts as the central enabler of machine learning and AI initiatives across the organization. Its mission is to reduce operational overhead and maximize ROI from ML use cases. As the backbone of ML operations, the team builds and maintains critical infrastructure, including feature stores, model deployment pipelines, 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.

• Design and maintain automated pipelines for both traditional ML models and modern AI systems including LLMs, multimodal models, and AI agents
• Implement robust CI/CD practices for model training, fine-tuning, evaluation, and deployment across diverse AI workloads
• Orchestrate seamless deployment of models, AI agents, and inference endpoints with automated testing and rollback capabilities
• Build and maintain infrastructure for large language model inference, fine-tuning, and serving at scale
• Implement comprehensive monitoring for model performance, drift detection, AI safety metrics, and responsible AI compliance
• Evolve operational processes to support both traditional ML and cutting-edge AI technologies

• 7+ years of industry experience building and deploying production-grade AI/ML systems.
• Recent hands‑on engineering experience with AI/LLM infrastructure and tooling (pure ML modelling is not required).
• Strong proficiency with Python, and familiarity with Scala, Go, or Rust
• Cloud platform expertise with AWS, GCP, or Azure, including AI‑specific services (Sage Maker, Vertex AI, Azure AI)
• Databricks platform experience with Unity Catalog, MLflow, and Databricks Machine Learning for end‑to‑end AI/ML workflows
• Modern ML infrastructure experience with tools like MLflow or similar platforms
• Containerization & 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 any other IaC tool of choice
• Distributed computing experience with Databricks, Ray, or Spark for large-scale AI workloads
• AI safety & governance experience with model evaluation, bias detection, and responsible AI practices
• Multi‑modal AI experience with vision‑language models, speech processing, or other modalities
• Experience at the Tier‑1 product company or related experience working within the product organisation

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.

We support…