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We are seeking a security researcher, who enjoys unraveling the mysteries and unique patterns of corporate computing environments and attackers techniques in Microsofts enormous scale of signals and security mechanisms, to join our Israeli research team and help provide our customers with tools to improve their security posture. The job includes performing both low level and high-level research of attackers techniques, security mechanism and controls, and data analysis over various types of telemetries.

Responsibilities include:

Analyze and research security controls, attackers techniques and anomalous patterns
Explore massive amounts of data to come up with new security posture insights, which can then be translated into security recommendations for our customers
Work together with the different engineering teams to develop the code to support the research findings
Collaborate with multiple product teams to design sensors, implement discovery & detection logics and validate their effectiveness using a data-driven approach
Collaborate with data science teams to understand and identify detection gaps, capabilities, assumptions and improvements
Collaborate with other teams across Microsoft and come up with innovative ideas which should be part of future versions of the product

We are looking for AI Engineer to join the Data Science team.

As an AI Engineer in the Data Science team, you will be working closely with applied researchers on model optimizations, GPU and hardware, language-model optimizations in the Video and Language domains and more. Your code will reach Azure resources and extensions, and you will use various technology stacks with the latest tools and methodologies. You will be expected to ;break down problems, learn and develop, have an open mind, and have ownership all the way to production. Working in a multi-disciplinary team will require excellent communication skills and at the heart of it all, alignment with Microsoft values and endless curiousness.

This is a fast-paced, high-impact environment where technical depth and creative problem-solving are essential. The team is looking for a Senior Security Researcher who is passionate about cloud security and eager to contribute to Azure-wide initiatives. This role is ideal for individuals who thrive on tackling complex challenges and are committed to advancing the security posture of Microsoft Azure through research, innovation, and collaboration.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.



Responsibilities
Uncover vulnerabilities in critical Azure services, protocols, and architecture, including networking, storage, and compute.
Provide expert security guidance to Azure teams managing high-value services with large customer bases, helping to safeguard against potential threats.
Utilize artificial intelligence tools and techniques to enhance the speed and effectiveness of security research.
Work closely with other security teams across Microsoft to maximize risk mitigation efforts throughout the technology stack.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work

In Google Search, we're reimagining what it means to search for information any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities
Write and test product or system development code.
Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Design and implement solutions in one or more specialized Machine Learning (ML) areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.

SuperSonic is hiring a Staff Data AI Lead to lead our AI initiatives.As a Staff Data AI Lead you will be responsible for leading SuperSonic organization AI integration efforts and serving as the bridge between advanced AI technologies and our business needs, implementing cutting-edge Data & AI technologies, creating AI-driven strategies and integrating innovative AI solutions across multiple platforms.
What you'll be doing
Develop and execute AI strategies aligned with business objectives
Advise leadership on AI capabilities and potential applications
Guide teams in adopting AI tools and methodologies
Ensure ethical and efficient implementation of AI technologies
Design and oversee AI-driven process improvements
Collaborate with various departments to identify AI opportunities
Stay current with the latest AI trends and advancements
Conduct AI-related training and workshops for staff
Manage AI projects from conception to implementation
Evaluate and recommend AI tools and platforms
Leading a team of AI engineers