Lead ML Ops Developer

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’re hiring a Data Science Lead in London to build and lead our Predictive Growth Optimisation team – pioneering ML models that power our user acquisition strategy, predict lifetime value, and optimise our $25M+ annual marketing spend across channels. This role owns the strategy, development, and continuous improvement of Flo’s pLTV system - a mission-critical model reused across UA, AdTech, personalisation, and financial forecasting. That is the core of the role. Alongside it, you'll stand up a Marketing Mix Modeling (MMM) capability to measure cross-channel effectiveness and inform budget allocation, and develop the algorithms to drive real-time UA campaign management. You'll lead a team building production systems that directly impact our growth trajectory, staying as hands-on as you choose. WHAT YOU’LL DO * Lead & develop a team of 6+ ML and Backend engineers - hiring, mentoring, and setting technical direction * Own pLTV strategy - architect and evolve our core predictive lifetime value models that inform millions in UA decisions * Stand up MMM - build our Marketing Mix Modeling capability: adstock and saturation modelling, channel contribution, and budget allocation, calibrated against our incrementality experiments * Power real-time campaign management - develop the algorithms that optimise our UA campaigns across channels in real time * Build production ML systems - from real-time prediction services handling millions of daily predictions to MMM models * Drive cross-functional impact - partner with Growth, Product, and Finance to translate business problems into ML solutions * Shape technical architecture - guide MLOps infrastructure, monitoring, and rapid iteration cycles * Stay as hands-on as you choose - modeling, architecture decisions, technical problem-solving; your call how deep you go. WHAT YOU BRING Technical Leadership * 7+ years applied ML experience building and deploying models in production * 4+ years managing technical teams (ML engineers, data scientists, or similar) * Expert knowledge of ML fundamentals: supervised/unsupervised learning, time series; strong grounding in causal inference * Experience with modern ML frameworks (TensorFlow, scikit-learn, CatBoost) Growth & Product Experience * Experience with growth analytics, attribution modeling, or marketing effectiveness * Understanding of user acquisition funnels and retention optimization * Comfortable translating business requirements into technical roadmaps * Strong communication skills - can explain complex models to executive stakeholders Production ML Systems * Experience deploying ML models at scale * Knowledge of MLOps practices: model versioning, monitoring, automated retraining * Understanding of data engineering fundamentals and cloud platforms NICE TO HAVE * Hands-on experience building Marketing Mix Models end to end, Bayesian or regression based * Background in consumer tech, mobile apps, or health tech * Knowledge of privacy-preserving ML techniques and A/B testing methodology 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 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 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. Read our privacy notice for job applicants.

ReqID: FEQ327R328 Recruiter: Kanwal Matharu Location:  London, United Kingdom - Hybrid Skills: Data Science, Machine Learning, AI, LLM, GenAI As a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as an ML expert. You will be reporting to the Manager, Field Engineering (Specialist Team) The impact you will have: * Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services. * Provide advanced technical support to the Solution Architects during the technical sales cycle by building MVPs, leading deep-dive technical sessions, and strategically aligning ML/data science solutions to complex customer business challenges using relevant real-world examples. * Serve as the trusted technical advisor for customers developing GenAI solutions, specializing in the design and implementation of RAG architectures on enterprise knowledge bases, enabling natural language querying of structured data, and establishing content generation and monitoring frameworks. * Drive community growth and platform adoption through thought leadership activities, including the creation of technical tutorials and training materials, as well as leading hackathons and presenting at industry conferences. What we look for: * Experienced, technical, customer-facing, and with a background in Data Science / Machine Learning, and Data Engineering.  Looking to learn and develop in a customer-facing technical role as a subject matter expert (SME) in a pre-sales environment. * Pre-sales or post-sales experience working with external clients across a variety of industry markets Data Science/ML Skills * Hands-on industry ML experience in at least one of the following: * ML Engineer: Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring * Data Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI * Hands-on experience working with Distributed Spark based systems. * Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience * Experience communicating and teaching technical concepts to non-technical and technical audiences alike * Passion for collaboration, life-long learning, and driving our values through ML * [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role * [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets * Can meet expectations for technical training and role-specific outcomes within 3 months of hire * Can travel up to 30% when needed About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.