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Our Tel-Aviv team develops machine-learning models that serve billions of buyers daily. To do so, we develop state-of-the-art recommendation and ranking systems. We work closely with domain experts to design features and embedding spaces best fitted for eCommerce. Finally, we use Meta's cutting-edge generative models to personalize the experience for our buyers.
Our team also builds AI capabilities to enhance Metas product catalogs to improve ads performance. Catalog-powered ads account for a significant portion of Metas revenue, with unlocking deep semantic understanding of our products being a key strategic lever for revenue growth.
If you're passionate about ML at scale and want to work with an amazing group of people - look no further - come and join us!
Software Engineer, Machine Learning Responsibilities
Leading projects or small teams of people to help them unblock, advocating for ML excellence
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmaps
Code deliverables in tandem with the engineering team

We are looking for researchers and applied scientists to join the Central Applied Science team. Central Applied Science is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally contribute to Meta's success. By applying your expertise in quantitative methods, you will be empowered to drive impact across a range of products, infrastructure and company operations. Individuals in this role are expected to have expertise and publications within research areas including artificial intelligence, machine learning, statistics, causal inference and experimentation. The ideal candidate will have a passion for building data-driven products and forming research frameworks to solve challenging, real-world problems.
Research Scientist, Central Applied Science (PhD) Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products.
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure.
Learn new tools, systems, and programming languages quickly as required by the particular project you are working on
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Communicate best practices in quantitative analysis to partners.
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value.
Publish research results in top-tier conferneces and at leading journals
Actively identify new opportunities within Meta's long term roadmap for data science contributions.

We are using a variety of ML and stats models and algorithms, from classic supervised learning, to anomaly detection, unsupervised learning and semi supervised learning, to detect and mitigate ongoing fraud campaigns.

In our solutions we are using Graph Neural Networks, Ensembles, Boosting, Regression models, Time Series data, Causal Inference and more.
Software Engineer, Machine Learning (Tel Aviv) Responsibilities
Leading projects or small teams of people to help them unblock, advocating for ML excellence.
Develop highly scalable classifiers and tools leveraging machine learning, data, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmaps
Code deliverables in tandem with the engineering team

In Shop Ads, we personalize sellers' shops to delight our buyers' and satisfy their needs. From the products to the text and media that complement them, the layout that makes it most accessible - every decision has the buyer in mind.
Our Tel-Aviv team develops machine-learning models that serve billions of buyers daily. To do so, we develop state-of-the-art recommendation and ranking systems. We work closely with domain experts to design features and embedding spaces best fitted for eCommerce. Finally, we use Meta's cutting-edge generative models to personalize the experience for our buyers.
Our team also builds AI capabilities to enhance Metas product catalogs to improve ads performance. Catalog-powered ads account for a significant portion of Metas revenue, with unlocking deep semantic understanding of our products being a key strategic lever for revenue growth.
If you're passionate about ML at scale and want to work with an amazing group of people - look no further - come and join us!
Software Engineer, Machine Learning Responsibilities
Play a role in setting the direction and goals for the ML pillar, in terms of project impact, ML system design, and ML excellence.
Owning the entire development cycle, from ideation to realization across the stack. Designing and developing machine learning models using supervised, unsupervised, and deep learning techniques.
Implementing and testing machine learning models in a production environment
Take part in the overall team engineering efforts and contribute with hands-on work
Working with software engineers to integrate machine learning models into applications and systems
Collaborating with data scientists to identify and select appropriate machine learning algorithms and techniques