At a Glance
- Tasks: Own the AI/ML pipeline and manage code, datasets, and models for innovative health solutions.
- Company: Join Flo, the world’s #1 health & fitness app, on a mission to revolutionise female health.
- Benefits: Enjoy competitive salary, flexible working, paid sabbaticals, and wellness perks.
- Why this job: Make a real impact in digital health with cutting-edge AI technology and a supportive team.
- Qualifications: 7+ years in AI/ML systems, strong Python skills, and cloud platform expertise.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Flo is the world’s #1 health & fitness app on a mission to build a better future for female health. With 6M 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.
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.
You’ll be responsible for:
- Designing and maintaining automated pipelines for both traditional ML models and modern AI systems including LLMs, multimodal models, and AI agents.
- Implementing robust CI/CD practices for model training, fine-tuning, evaluation, and deployment across diverse AI workloads.
- Orchestrating seamless deployment of models, AI agents, and inference endpoints with automated testing and rollback capabilities.
- Building and maintaining infrastructure for large language model inference, fine-tuning, and serving at scale.
- Implementing comprehensive monitoring for model performance, drift detection, AI safety metrics, and responsible AI compliance.
- Evolving operational processes to support both traditional ML and cutting-edge AI technologies.
Your Experience Must have:
- 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 (SageMaker, 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.
Nice to have:
- 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.
What you’ll get:
- 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.
MLOps engineer employer: Flo Health Inc.
Contact Detail:
Flo Health Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with MLOps engineers on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI/ML pipelines and CI/CD processes. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common MLOps scenarios and challenges. Be ready to discuss how you've tackled similar issues in the past, and don’t forget to highlight your experience with cloud platforms and modern ML infrastructure.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our mission at Flo.
We think you need these skills to ace MLOps engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI/ML systems. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Show Off Your Technical Skills: We’re looking for someone with solid experience in Python and cloud platforms like AWS or GCP. Be specific about your technical expertise and any tools you’ve used, especially those related to ML infrastructure.
Be Clear and Concise: When writing your application, keep it straightforward. Use bullet points where possible to make it easy for us to read through your qualifications and experiences quickly.
Apply Through Our Website: Don’t forget to submit your application through our official website! It’s the best way for us to receive your details and ensures you’re considered for the role.
How to prepare for a job interview at Flo Health Inc.
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and cloud platforms like AWS or GCP. Brush up on your experience with tools like Databricks and MLflow, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built or deployed AI/ML systems. Highlight your role in designing automated pipelines or implementing CI/CD practices. Real-world examples will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Company’s Mission
Familiarise yourself with Flo's mission to enhance female health through AI-powered solutions. Be ready to discuss how your skills can contribute to this goal and why you’re passionate about working in the health and fitness space.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current AI initiatives, challenges they face in ML operations, or how they ensure compliance and safety in AI. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.