Facebook Applied Research Scientist, Machine Learning - Auction & Delivery in Helena, Montana
Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.
The massive scale and heavy engagement of the people using our products make the Meta family of products (Instagram, Messenger, Oculus, WhatsApp, among others) an ideal place for advertisers to build their brands and drive results. Our advertising auction is the system marketers use to do that - an automatic system that optimizes which ads to display to users and determines how much advertisers should pay for them. This system produces billions of predictions and processes billions of transactions per day, generating an enormous amount of data. The successful candidate will gain an understanding of the Machine Learning algorithms to power Meta monetization and drive meaningful improvements in modeling.The Model Understanding team sits within the broader Monetization Applied Research & Strategy organization. The team is made up of Applied Research Scientists with a diverse set of backgrounds. Specifically, we have team members with various levels of academic attainment (Bachelor's, Master's and PhD), work experience and professional backgrounds. As this team is fundamentally focused on machine learning R&D, the candidate must be comfortable with ambiguity and answering broad research questions in machine learning. They would be intellectually curious, a great communicator, data-driven, a fast learner and able to move fast while keeping focused on high impact projects. Applicants should have a strong quantitative understanding, and a talent for taking complex concepts and distilling them into clear, accessible learnings.
Lead research to advance the science and technology of intelligent machines.
Research applied machine learning questions in our ads system to improve prediction accuracy and drive advertiser value.
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Contribute research that can be applied to Facebook product development.
Develop an understanding of the auction, analyze current performance and identify opportunities to improve the system.
Work closely with engineering and product teams to develop hypotheses, run experiments and prototype new product ideas.
Bachelor's Degree in Computer Science, Electrical Engineering, Math, Statistics, or other quantitative fields.
Experience working with machine learning algorithms and AI Systems.
Experience operating independently and delivering results.
Extensive experience with Python and ML modeling frameworks such as PyTorch or TensorFlow.
Understanding of statistical data analysis (e.g. regression, probability).
Experience with recommendation systems (e.g. ads, e-commerce).
Expertise in identified research areas such as artificial intelligence, machine learning, computational statistics, and applied mathematics.
Equal Opportunity: Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at email@example.com.