Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Within Monetization (Ads), the Experimentation team is responsible for Measurement Statistics, Measurement Correctness, and Measurement Infrastructure, which underpins model-based experimentation. Every change to our models is deployed via an experiment and measured for improvements to quality (for our 3Bn+ monthly active users) and value (for millions of advertisers). We are at the heart of Meta's growth, driving significant step changes in a domain operating at significant scale. We are seeking an experienced and mathematically skilled Machine Learning Engineer to join our Experimentation team. This is a leadership hire focused on solving high-impact business challenges in experimentation. You will advance our approach on how we approach launch decisions, optimize launch models, and significantly reduce uncertainty in our experimentation. This role offers an opportunity to solve open and challenging problems and deliver a step change in ML Experimentation.

Key responsibilities include driving the development of new adaptive experimentation techniques, leading efforts to improve the sensitivity and trustworthiness of our experimentation platform, and developing solutions for open problems at the cutting edge of experimentation measurement, such as addressing selection bias due to user opt-outs. You will collaborate closely with Core ML research scientists and product teams (e.g., Instagram) to ensure seamless integration and avoid revenue interference. Applying deep mathematical and statistical expertise, you will build robust models based on opt-in user data and contribute to ensuring the quality of ads meets defined benchmarks for users while delivering maximum value for advertisers. Ultimately, your work will help connect businesses to people through better, more relevant advertisements.

Experience
- Strong mathematical and statistical background, including probability and statistical theory
- Proficiency in Python programming
- Experience with data analysis across large datasets
- Software engineering skills combined with statistical and mathematical expertise
- Experience navigating large enterprise architectures, identifying issues, and implementing nuanced changes
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Experience with Machine Learning emphasizing statistical and mathematical foundations
- Experience with experimentation platforms and A/B testing infrastructure
- Track record of staying current with the latest research advancements in experimentation and measurement

About you
Analytical and mathematically skilled professional with leadership capabilities, passionate about solving high-impact business challenges in experimentation. You are collaborative, able to work closely with research scientists and product teams, and committed to delivering trustworthy and sensitive experimentation platforms. You stay updated with emerging AI technologies and are dedicated to ethical AI practices.

Qualifications
Relevant academic background in mathematics, statistics, computer science, or related fields is expected. Proven experience in machine learning engineering with a strong emphasis on statistical and mathematical foundations is required.