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At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities
Design and Build ML Infrastructure: Develop and maintain scalable, production-ready infrastructure for both traditional ML (anomaly detection, user behavior analytics) and LLMs across enterprise environments.
Optimize Model Performance: Analyze and optimize LLM and ML performance using techniques like knowledge distillation, quantization, and efficient data structures to boost efficiency and lower resource costs.
Deploy and Integrate: Collaborate heavily with software and data engineers to integrate models into production pipelines, cloud-native environments, and on-premises workflows.
Drive MLOps & Tooling: Manage the complete model lifecycle (monitoring, retraining, deployment) and actively build custom tools from scratch to improve the team's ML workflows.
Elevate Engineering Standards: Perform rigorous code reviews, ensure robust Python production standards, and provide technical guidance to data scientists and junior engineers.
Cross-Functional Partnership: Partner with cybersecurity researchers and product teams to translate research insights and threat analysis features into highly performant production code.
Open-Source Engagement: Actively engage with the open-source community by contributing code and expertise to relevant ML/LLM projects.

At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities:
Own and operate the company authentication platform and internal IdP (token issuance, rotation, validation).
Build and maintain the NuGet packages for token validation and service-to-service communication used across all services.
Manage API gateway policies (routing, auth, rate limits, mTLS, observability).
Define and enforce RBAC across services (roles, permissions, policy evaluation, audits).
Continuously improve reliability, performance, and developer experience through automation, documentation, and support.

At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities:
Define the product roadmap needs into detailed requirements, work with R&D teams and manage the entire development process from concept to launch.
Serve as an in-house subject matter expert of our company platform and become the go-to person in your domain.
Work closely with engineering teams to ensure high-quality deliverables.
Manage strategic relationships with new and existing partners.

Were looking for a strategic and experienced product leader to drive our data classification and privacy portfolio-one of the most foundational parts of our platform and a critical area of investment and innovation. This role is responsible for building advanced, scalable solutions that help our customers identify, categorize, and govern sensitive data across SaaS, IaaS, and on-prem environments.
You will lead a talented team of product managers and work closely with engineering, design, marketing, and sales to ensure our classification and privacy products continue to set the industry standard. Youll work in a hybrid model, and help shape the future of the company platform.
Responsibilities
Lead the strategy, vision, and execution for our companys classification and privacy products portfolio
Manage and grow a team of experienced product managers across multiple product lines
Define and own the roadmap for sensitive data discovery, classification, labeling, and privacy-aware controls across cloud and on-premises environments
Deeply understand customer use cases for compliance (e.g., GDPR, CCPA, HIPAA), data governance, insider threat protection, and data loss prevention
Drive innovations in content-aware and context-aware classification, including AI-driven techniques such as ML, NLP, and LLM-based models to accurately identify and categorize sensitive data
Evaluate and incorporate emerging technologies (e.g., generative AI and large language models) to enhance classification accuracy, scalability, and real-time data understanding
Work hands-on with UX designers, engineering, and research teams to design thoughtful, scalable solutions
Partner with internal stakeholders including Customer Success, Sales Engineering, and Professional Services to understand deployment challenges and inform roadmap priorities
Engage regularly with customers and prospects to gather feedback and validate product direction
Collaborate with marketing and sales teams to position, launch, and drive adoption of new features and products
Track and analyze product usage, customer feedback, and market trends to iterate on product strategy
Serve as a subject matter expert and thought leader both inside and outside the organization on data classification and privacy topics.

We are looking for a Knowledge & AI Enablement Manager with proven experience in Knowledge Management and AI driven systems to design, build, and own the complete Knowledge Lifecycle for Technical Support.
This role defines how operational knowledge is created, governed, maintained, and embedded into daily Support workflows, while ensuring it is AI ready and serves as a trusted, high quality input for AI models across the organization.
Key Responsibilities:
Knowledge Lifecycle Ownership:
Own and build the end-to-end Knowledge Lifecycle for Support, from case-driven knowledge creation through continuous improvement and reuse
Define how knowledge is captured from cases, incidents, and escalations and transformed into structured, reusable, high-impact assets
Establish governance models for knowledge quality, validation, ownership, versioning, and ongoing maintenance
Design and operationalize workflows that embed knowledge creation, review, and updates into daily Support activitie
Define and implement a RACI model for knowledge creation, review, approval, and maintenance
Knowledge and AI Readiness:
Own KM platform configuration, Search and analytics tooling, taxonomy, publishing workflows, and integration with case management and AI retrieval pipelines
Define and enforce standards that ensure Support knowledge is structured, tagged, and maintained to be fully consumable by AI systems such as LLMs, RAG pipelines, semantic search, automation, and recommendation engines
Partner closely with Data, AI, and Engineering teams to align knowledge models, structure, and lifecycle with AI consumption requirements and future AI roadmaps
Act as the primary owner of the Support knowledge layer that feeds AI, ensuring consistency, reliability, and scalability
Measurement, Feedback, and Adoption
Define, track, and continuously improve KPIs including knowledge coverage, freshness, reuse, case deflection, and measurable AI performance impact
Establish feedback loops that surface insights from AI usage and knowledge gaps back to Support Engineers, driving better case handling and higher quality knowledge creation
Lead change management initiatives to drive adoption, accountability, and consistent knowledge behaviors across global Support teams.

Power the Future with us! At our company, we're a global leader in smart energy technology, with over 3,000 employees, offices in 30 countries, and millions of installations worldwide. Our innovative solutions include solar inverters, battery Storage, backup systems, EV charging, and AI-based energy management. We're committed to making clean, green energy the primary power source for homes, businesses, and beyond. With the growing demand for electricity, the need for smart, clean energy sources is constantly rising. our company offers amazing opportunities to develop your skills in a multidisciplinary environment, covering everything from research and development to production and customer supply. Work with talented colleagues, tackle exciting challenges, and help create a sustainable future in an industry that's always evolving and innovating. Join us and be part of a company that values creativity, agility, and impactful work. As a Sales data Analyst at our company, you will support our sales team by compiling and analyzing sales data, providing valuable feedback and actionable insights to guide sales activities. You will champion data collection and present reports and conclusions to the management team. This role requires a strong understanding of our products and business processes, technical abilities, and a high level of accuracy. It offers a unique opportunity to gain hands-on experience in sales analysis and contribute to the success of our company. Key Responsibilities
* Compile, analyze, and report sales data.
* Drive data collection and data cleansing activities, ensuring data integrity and accuracy.
* Monitor and analyze sales performance, customers behavior, determine sales potential, and issue recommendations.
* Provide actionable insights to the sales team and stakeholders.
* Prepare and present reports on data trends and sales performance.
* Develop and maintain BI dashboards and databases to visualize sales data and trends.
* Lead IS automation solutions for managing sales data.
* Collaborate with other departments to understand data needs.
* Provide administrative support to the sales team as needed.
Country:
Israel
City:
Herzliya

We are looking for a QA & Automation Engineer to take ownership of quality across our embedded and hardware-integrated products.
This role combines hands-on system validation with building scalable test automation to ensure reliability from firmware to full device operation.
Responsibilities
Define and execute end-to-end test plans for embedded systems and connected devices
Design and implement automated test frameworks to improve coverage and efficiency
Validate firmware behavior, communication protocols, and system-level performance
Collaborate closely with firmware, hardware, and software teams to debug and resolve issues
Integrate automated testing into CI/CD pipelines and release processes
Drive continuous improvement of QA methodologies, tools, and best practices

Responsibilities
Responding to customer inquiries across various channels
Handling, tracking, and documenting customer cases in internal systems
Coordinating with relevant company teams as needed
Meeting defined targets and service-level agreements (SLA)
Combining customer-facing communication with back-office operational tasks
Suitable for students, including part-time positions
Hybrid work model based in Herzliya

Join us as a Full-Stack Developer and help build modern, scalable web applications that power real user experiences. Were looking for someone who loves turning complex problems into elegant solutions using TypeScript, Node.js, and React. In this role, youll work on everything from crafting rich, data-driven interfaces to designing reliable backend services and APIs. If you enjoy clean code, strong architecture, and building products that scale, this is a great opportunity to make an impact alongside a collaborative and talented engineering team

What Youll Do
Develop and maintain full-stack web applications using modern Node.js and React frameworks
Build scalable and intuitive user interfaces, including complex components and large data-driven views
Design and maintain REST APIs, including validation, authentication, and documentation
Work with relational databases to design schemas and optimize queries
Implement modern state management solutions across frontend and backend services
Ensure high-quality code through automated testing (Unit, Integration, E2E)
Collaborate with engineers, designers, and product teams to deliver reliable and scalable features

This role is designed for a true automotive expert - someone with deep hands-on and theoretical understanding of vehicle mechanics, electronics, ECUs, diagnostics, and communication networks - who can leverage that expertise to develop new tools, capabilities, and predictive models for future vehicle fault detection.
You will serve as a professional authority in the automotive domain, translating real-world vehicle behaviour and failure mechanisms into innovative technological solutions.
Beyond supporting installations and customers, this position plays a critical role in shaping the next generation of predictive maintenance capabilities by transforming automotive knowledge into system logic, analytical tools, and fault prediction models.
Your D2D will include
Leverage deep automotive knowledge to develop new system capabilities and predictive maintenance tools
Identify commercial vehicle mechanical and electrical failure patterns and translate them into system logic and predictive models
Investigate vehicle CAN bus data and sensor data to extract engineering insights
Define failure scenarios and convert them into structured diagnostic and analytical frameworks
Work closely with algorithm, software, and data teams to design and refine predictive models
Conduct controlled field experiments and build detailed technical reports
Investigate complex product and vehicle malfunctions
Provide advanced technical support and professional guidance to customers
Prepare installation manuals and technical documentation
Deliver technical training to internal teams, distributors, and customers
Stay up to date with emerging technologies and trends in the automotive industry