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We are looking for an AI Specialist to explore and implement practical AI solutions that drive smarter decisions, automate workflows, and unlock new opportunities for our business.
Youll be the person who transforms curiosity into impact testing tools, integrating technologies, and guiding how AI can bring real value to our teams and operations.
In this role, your responsibilities will Include, but wont be limited to:
AI Exploration & Implementation:
- Identify opportunities where AI can improve processes and decision-making.
- Explore, test, and integrate AI tools and technologies into workflows.
- Create proof-of-concepts and small-scale pilots to demonstrate value quickly.
Data & Insights:
- Work with large datasets to uncover patterns, trends, and actionable insights.
- Translate business needs into simple, clear AI solutions that solve real problems.
- Document processes and learnings so teams can build on your work.
Optimization & Support:
- Monitor and maintain AI tools and workflows to ensure they consistently deliver results.
- Troubleshoot issues and refine solutions to improve efficiency and accuracy.
- Stay up to date with emerging AI trends and bring new ideas to the team.

we are seeking a senior AI Researcher to join its R&D group and lead the frontier of large-scale LLM optimization. You will focus on maximizing performance, scalability, and efficiency of LLM training and inference across massive GPU clusters, bridging deep learning research, distributed systems design, and hardware-aware optimization.
At our company, we treat AI performance as a systems problem. Just as we reinvented networking through disaggregation and software-defined scale, were applying the same philosophy to AI infrastructure. Your work will directly influence how large models are deployed, scaled, and optimized across high-density compute environments.
Responsibilities
Research, design, and implement new optimization strategies for large-scale LLM training and inference (e.g., tensor/pipeline/expert parallelisms, quantization, prefill/decode disaggregation, GPU communication optimization).
Profile distributed training and inference pipelines to identify algorithmic, memory, and scheduling inefficiencies.
Collaborate closely with systems, compiler, and infrastructure teams to co-design efficient communication topologies, memory management, and runtime scheduling.
Develop internal tools for huge-scale LLM benchmarking, profiling, and automatic tuning.
Validate research through measurable impact, higher throughput, better FLOPS utilization, improved convergence efficiency, or reduced compute cost.
Present research and engineering results to internal and external technical audiences.

our company was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at our company offers countless ways to make an impact in a fast growing organization. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Code Generation (PhD) (Tel Aviv) Responsibilities
Develop novel state-of-the-art computer vision algorithms and corresponding systems, leveraging various deep learning techniques.
Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms. Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
Devise better data-driven models for information retrieval, Multi-modal fusion, generation or media understanding (CV, NLP, Speech/ Audio).
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Contribute to research that can be applied to our company product development.

Central Applied Science (CAS) is a research and development team, working to improve our companys products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the company family of apps. The work we do enhances the company family of apps that enable billions of people to communicate with each other daily. Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, and economics among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at our company and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise. We are looking for research interns to join the Product Algorithms team in Central Applied Science. The team is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally increase the magnitude of our companys successes. The ideal candidate will have extensive graduate training in computer science, machine learning, or related disciplines, and the passion to solve real world hard scientific problems. By applying your expertise and passion you will be empowered to drive impact across a range of products, infrastructure and operational use cases at our company. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, 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 our company's unparalleled data infrastructure.
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.

About the position As a Red Team Specialist focused on Generative AI Models, you will play a critical role in enhancing the security and integrity of our cutting-edge AI technologies. Your primary responsibility will be to conduct analysis and testing of our generative AI systems, including but not limited to language models, image generation models, and any related infrastructure. Your objective is to help clients secure their AI models and frameworks by identifying weaknesses, assessing risks, and providing clear steps for improvement.
Key Responsibilities:
* Simulated Cyber Attacks: Conduct sophisticated and comprehensive simulated attacks on generative AI models and their operating environments to uncover vulnerabilities.
* Vulnerability Assessment: Evaluate the security posture of AI models and infrastructure, identifying weaknesses and potential threats.
* Risk Analysis: Perform thorough risk analysis to determine the impact of identified vulnerabilities and prioritize mitigation efforts.
* Mitigation Strategies: Collaborate with development and security teams to develop effective strategies to mitigate identified risks and enhance model resilience.
* Research and Innovation: Stay abreast of the latest trends and developments in AI security, ethical hacking, and cyber threats. Apply innovative testing methodologies to ensure cutting-edge security practices.
* Documentation and Reporting: Maintain detailed documentation of all red team activities, findings, and recommendations. Prepare and present reports to senior management and relevant stakeholders.

Required Manager 3, AI Science
Job Overview
Manage a global group of AI scientists teams dedicated to developing and deploying AI solutions that help ensure Trust and Safety across our products and services. Drive research, development, and implementation of advanced AI along with ML technologies, while fostering a collaborative and innovative environment.
Responsibilities
Lead global AI Science teams, specializing in Fraud and Content Moderation.
Recruit and mentor top AI Scientists in Israel and US.
Apply AI/ML to address Fraud and content issues, driving innovation and growth.
Deliver impact through data-driven insights and advanced analytics.
Provide technical and strategic leadership in AI science.
Inspire AI innovations to enhance platform safety and fraud detection.
Guide business stakeholders to interpret and utilize AI-first solutions and research findings.

Required Senior AI Scientist
Job Overview
The Content Safety Team, which is responsible for ensuring a safe environment for our customers, is seeking a Senior AI Scientist. The team develops content moderation solutions for user-generated and AI-generated content across all our products and utilizes advanced GenAI tools to build capabilities such as automatic labeling.
We encourage you to apply if you
Are passionate about using advanced ML techniques and evolving technology to create a safe environment for customers
Love working as part of a team of experienced AI scientists that love research and innovation just as much as they love getting models to production and making an impact
Are interested in partnering with analysts and researchers to implement your ideas into mitigation policies that keep the bad actors away
Take pride in having end to end ownership of your models - from conception, throughout research and development to production and monitoring
Responsibilities:
Develop and refine content moderation models to filter and tackle abusive content across various products, content types and modalities.
Work extensively with NLP algorithms, focusing on fine-tuning transformers and large language models (LLMs) to enhance accuracy and efficiency.
Explore and integrate advanced technologies such as Retriever-Augmented Generation (RAG) and Agentic AI to assist in the automatic labeling and classification of data.
Collaborate with a multi-disciplinary team including machine learning engineers, AI scientists, and policy experts to ensure models align with ethical standards and company policies.
Stay updated with the latest research in AI and machine learning to incorporate cutting-edge techniques into content moderation strategies.
Prepare and maintain documentation on model development, configurations, and performance metrics for both technical and non-technical audiences.
Mentor and guide junior AI scientists, fostering a collaborative and productive team environment.

We are seeking an experienced and detail-oriented Red Teaming team lead to oversee complex research and delivery efforts focused on identifying and mitigating risks in Generative AI systems. In this role, you will lead a multidisciplinary team conducting adversarial testing, risk evaluations, and data -driven analyses that strengthen AI model safety and integrity. You will be responsible for ensuring high-quality project delivery, from methodology design and execution to client communication and final approval of deliverables. This position combines hands-on red teaming expertise with operational leadership, strategic thinking, and client-facing collaboration. Key Responsibilities Operational and Quality Leadership
* Oversee the production of datasets, reports, and analyses related to AI safety and red teaming activities.
* Review and approve deliverables to ensure they meet quality, methodological, and ethical standards.
* Deliver final outputs to clients following approval and provide actionable insights that address key risks and vulnerabilities.
* Offer ongoing structured feedback on the quality of deliverables and the efficiency of team workflows, driving continuous improvement. Methodology and Research Development
* Design and refine red teaming methodologies for new Responsible AI projects.
* Guide the development of adversarial testing strategies that target potential weaknesses in models across text, image, and multimodal systems.
* Support research initiatives aimed at identifying and mitigating emerging risks in Generative AI applications. Client Engagement and Collaboration
* Attend client meetings to address broader methodological or operational questions.
* Represent the red teaming function in cross-departmental collaboration with other teams.
About us:
We are the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the worlds largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, we empower security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, we enable organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.
Hybrid:
Yes

We are seeking an experienced and detail-oriented Red Teaming team lead to oversee complex research and delivery efforts focused on identifying and mitigating risks in Generative AI systems. In this role, you will lead a multidisciplinary team conducting adversarial testing, risk evaluations, and data -driven analyses that strengthen AI model safety and integrity. You will be responsible for ensuring high-quality project delivery, from methodology design and execution to client communication and final approval of deliverables. This position combines hands-on red teaming expertise with operational leadership, strategic thinking, and client-facing collaboration.
Key Responsibilities
Operational and Quality Leadership
* Oversee the production of datasets, reports, and analyses related to AI safety and red teaming activities.
* Review and approve deliverables to ensure they meet quality, methodological, and ethical standards.
* Deliver final outputs to clients following approval and provide actionable insights that address key risks and vulnerabilities.
* Offer ongoing structured feedback on the quality of deliverables and the efficiency of team workflows, driving continuous improvement. Methodology and Research Development
* Design and refine red teaming methodologies for new Responsible AI projects.
* Guide the development of adversarial testing strategies that target potential weaknesses in models across text, image, and multimodal systems.
* Support research initiatives aimed at identifying and mitigating emerging risks in Generative AI applications. Client Engagement and Collaboration
* Attend client meetings to address broader methodological or operational questions.
* Represent the red teaming function in cross-departmental collaboration with other teams.
About us:
We are the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the worlds largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, we empower security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, we enable organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.
Hybrid:
Yes.