Senior/Lead Machine Learning Engineer (Predictions)

Senior/Lead Machine Learning Engineer (Predictions)

London

We’re very proud of our achievements:

In July 2024, we secured a $200M investment led by General Atlantic to help revolutionise women’s health, and became the first purely digital consumer women’s health app to achieve unicorn status!

We’ve had 380M+ downloads, have over 70M monthly users, are #1 by installs in the iOS Health category, hit 4.9 stars on the App Store (3M+ reviews), are backed by 9 VCs, had a 40% revenue increase last year, and topped a valuation of $1B.

We’re a growing, ambitious HealthTech business building the essential digital health partner of tomorrow to empower women, girls, and people who menstruate with the knowledge and support they need to stay well and live better.

Our cycle, ovulation and pregnancy tracking, educational content and anonymised community platform have been trusted for years by millions to help them feel more in control of their health every day.

Now, we’re harnessing the power of data analytics and AI to build a smarter future, one where we all know our bodies better, with an aim to become the essential health partner to women worldwide.

The Job

We are Flo, the world’s most popular female health app! Our engineers aren’t just building a better product; they’re making the world a better place by improving female health. We leverage Machine Learning and AI to create a more personalised experience for our users, from providing more accurate cycle predictions to delivering relevant, personalised, and medically credible health insights.

We are looking for a Machine Learning Engineer to join the Predictions team. This team focuses on one of the cornerstone features of the Flo Health app: delivering accurate predictions to our users about their cycles and more. We develop state of the art solutions to provide the most accurate predictions to our users on the app. To do so, we leverage a range of different data points and machine learning techniques to ensure the best user experience. This role will focus on our menstrual cycle modelling, finding patterns and regularities in symptoms, symptom predictions, utilising data from wearable devices, and more. If you’re passionate about technology and driven by delivering value to users, we would love to hear from you!

Your Experience

Must have:

• Solid understanding of classical ML algorithms
• Demonstrated success in building and deploying large-scale machine learning models that serve users in real-time
• Ability to devise creative solutions to intricate technical challenges, including experience in systems design with the ability to architect and explain ML pipelines
• Strong Python programming skills for efficient model development and deployment
• Experience in building and managing data pipelines using tools like Apache Spark
• Familiarity with different feature engineering techniques
• Excellent communication skills and ability to collaborate with diverse teams
• Commitment to responsible AI practices, including fairness, accountability, and transparency

Nice to have:

• Advanced degree in Computer Science, Mathematics, or a related field
• Familiarity with statistical and measurement fundamentals (including time series analysis), and running and evaluating AB tests
• Strong data visualisation skills to help narrate stories from data
• Experience in the MedTech domain

What you'll be doing

You'll be responsible for:

• Explore, develop and test complex ML systems to improve female health by delivering more accurate and personalised insights to the users
• Work in a fast-paced environment, to quickly build and validate product hypotheses, taking end to end ownership of the ML products
• Constantly improve our technical capabilities by researching and implementing state of the art ML solutions that deliver value to users
• Work in a cross-functional setup alongside other engineering (ML, Backend, Frontend, QA), product, and analytics teams

Salary Range - per year

Salary ranges may vary depending on your skills, competencies and experience.

Reward

People perform better when they’re happy, paid well, looked after and supported.

On top of competitive salaries, Flo's employees have access to:

• A flexible working environment with the opportunity to come into the office and work from home
• Company equity grants through Flo’s Employee Share Option Plan (ESOP)
• Paid holiday and sick leave
• Fully paid female health and sick leave, in addition to holiday and regular sick leave
• Workations - an opportunity to work abroad for two months a year
• Six months paid maternity leave, and one months paid paternity leave (subject to qualifying conditions) inclusive of same-sex and adoptive parents
• Career growth, progression, and learning development resources
• Annual salary reviews
• Unlimited free premium Flo subscriptions
• A whole host of other benefits (health/pension/social schemes)

Our Culture

We’re problem solvers, we’re adaptable, we’re empathy driven and results led.

People here like working in a fast-paced, multi-national, multi-cultural and ever changing environment. Everyone has an impact on a powerful mission, and is happy to roll their sleeves up to ideate solutions and put them in place. Being part of a growing business means that sometimes it's not easy and we work hard, but our mission is always at the forefront of what we do.

Diversity, Equity and Inclusion

The strength of our workforce is in the diverse backgrounds of our employees, and Flo is committed to applying its equal opportunities policy at all stages of recruitment and selection. This means recruitment and selection of talent into Flo Health companies is only based on individual merit and qualifications directly related to professional competence. Shortlisting, interviewing, and selection will always be carried out without regard to gender identity or expression, sexual orientation, marital or civil partnership status, color, race, nationality, ethnic or national origins, religion or beliefs, ancestry, age, veteran status, mental or physical disability, medical condition, pregnancy or maternity status, trade union membership, or any other protected characteristics.

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