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The Cloud Guard research team is looking for a curious and highly motivated Cloud Security Researcher who will translate the research to direct security value for the company and product.

As a Cloud Security Researcher in the Cloud Guard area, you'll conduct ongoing research on different cloud infrastructures and services, detect and replicate different attacks, and publish technical blog posts.

Key Responsibilities
Initiate and conduct Cloud Research Initiatives throughout the realm of cloud cyber security.

Conduct cutting-edge research on all different cloud vendors and become an authoritative source of knowledge for the team.

Collaborate with cross-functional teams: Work closely with various teams to drive cloud detections in the product.

Publish intensive, technical blog posts on attack discovery and deep insights.

We are seeking a talented MLOps Engineer to join our innovative team. In this pivotal role, you'll be at the heart of our operations, bridging development, machine learning, and large language models (LLMs) to ensure seamless, efficient, and scalable deployment of our AI-driven solutions. If you're passionate about cutting-edge technology, excel in a dynamic environment, and are keen to make a significant impact, we're eager to connect with you!

Key Responsibilities
Collaboration: Work closely with ML engineers, data scientists, and software developers to integrate ML/LLM models into production.
Automation and Process Definition: Define work processes and implement automation pipelines to streamline ML/LLM development and deployment, enhancing productivity and efficiency.
Deployment and Scaling: Deploy, monitor, and scale machine learning models and large language model applications across various environments.
Monitoring and Maintenance: Implement monitoring solutions for performance and health of ML/LLM models, ensuring high availability and reliability.
Optimization: Continuously optimize ML pipelines for improved performance, scalability, and cost-efficiency. Security and Compliance: Ensure adherence to data privacy, security protocols, and compliance standards in ML/LLM operations.
Innovation: Keep abreast of the latest developments in DevOps, ML, and LLM technologies to drive continuous improvement and innovation.

Similarweb is the leading digital intelligence platform used by over 3500 global customers. Our wide range of solutions power the digital strategies of companies like Google, eBay, and Adidas.

We help our customers succeed in todays digital world by giving them access to data-driven insights, competitive benchmarks, strategic analysis, and more. In 2021, we went public on the New York Stock Exchange, and we havent stopped growing since!

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.

As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.

What does the day-to-day of a ML & Big Data Analyst at Similarweb look like:

Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of Similarwebs data and algorithms.
Utilize your deep understanding of Similarwebs data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.

Come join Intuit's AI organization as a Data Science Group Manager, leading our NLP Capabilities group.
Responsibilities
Lead multiple teams of data scientists and machine learning engineers
Mentor and hire the best data scientists in Israel
Apply artificial intelligence, generative artificial intelligence, and machine learning techniques to solve complex questions or fuel new business opportunities
Deliver breakthrough benefits to Intuit users and customers, across small business and consumer products using individual, enriched, and aggregated data
Provide leadership in advanced engineering, data science, and analytics in the development of current and future products or technologies
Provide technical leadership across multiple teams, by understanding a key technology space deeply enough to help guide strategy
Provide and inspire data science innovations that fuel the growth of Intuit
Understand and teach proven methods and hacking skills in working with divergent data types at scale, to explore and extrapolate data-driven insights, using advanced, predictive statistical modeling and testing applied to data acquired and cleansed from a range of sources
Provide the entrepreneurial guidance essential for business stakeholders to appropriately interpret and build on findings, and fully exploit the insights revealed through the research

Join the innovative NLP Capabilities AI group, to help build the next generation of awesome products and experiences using cutting-edge technology.

If you love having stretch goals, real-world challenges, and making customers incredibly happy while fostering your obsessive need for perfect code and user experience, this is the job for you.

Join our brand-new innovative team to help build the next generation of awesome products and experiences using cutting-edge technology.

In this role, you will:

Be a part of a vibrant team of Data Scientists and ML Engineers
Collaborate with many teams in Intuit and contribute to many components in different business units. We love engineers who lead the change, communicate with customers, and deliver the most beautiful and intuitive applications
Be expected to help architect, code, optimize, and deploy ML models at scale using the latest industry tools and techniques
Help automate, deliver, monitor, and improve ML solutions
Responsibilities
Design and build systems which improve machine learning scalability, usability, and performance.
Work cross functionally with product managers, data scientists, and engineers to understand, implement, refine, and design machine learning and other algorithms.
Effectively communicate results to peers and leaders.
Explore the state-of-the-art technologies and apply them to deliver customer benefits.
Interact with a variety of data sources, working closely with peers and partners to refine features from the underlying data and build end-to-end pipelines.

Adaptive cloud is a new and exciting domain, bridging the gaps between cloud environment and edge devices, so that our customers can run their workloads where it best suits them. This is an opportunity to influence the security of this domain, covering cloud security, OS environments, deployment challenges and end to end research.

The Edge & Platform Security Fundamentals (EPSF) org ensures we ship the world's most secure operating systems, cloud platforms, and edge devices. We conduct research into the highest priority attack surfaces and scenarios, including into Microsoft strategic investments such as Adaptive Cloud, AI, and next generation OS. Our research teams include leading researchers in this domain, finding and fixing critical issues, and developing techniques and tools that help us scale the security research.

Being part of EPSF IL, you will build a new team of security researchers tasked with helping Microsoft ship the most secure products in the new domain of Adaptive cloud. The ideal candidate will have broad experience in both cloud security research as well as OS and container security, and with leadership qualities to lead additional researchers in hands on research.
Responsibilities

Build a new security research team from the ground up, defining the targets and roadmap.
Lead the work of a security focused research team across multiple concurrent projects.
Perform strategic and independent security research, discover new bug classes and offensive techniques.
Collaborating with partner teams and organizations on research findings to maximize security impact.
Contribute to improving the security posture of Adaptive cloud products.
Evaluate tools, techniques, and procedures for feasibility, effectiveness, and impact.
Develop and refine offensive security knowledgebases, guides, and training.
Contribute to tooling and automation for security research, including bug discovery automation and analysis.