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We are looking for a Software Engineer specializing in ML systems Engineering to join Development department.
While vision and language models have become increasingly commoditized, proprietary deep learning models are unique, fast-evolving, and deployed in live trading across the worlds most efficient and sophisticated financial markets. Operating in this environment presents distinct scaling challenges and continuous opportunities for optimization. Success in this role requires first-principles thinking and a deep understanding of the engineering trade-offs behind high-performance DL systems.
This is a pivotal role within engineering organization. You will work closely with researchers and engineers across the company, running deep learning models on massive compute clusters and adapting them for production serving under strict and non-trivial constraints.

we are a leading semiconductor design center, developing SoCs, microcontrollers, and security hardware solutions for tier-1 customers in the computing and server space. As a self-contained R&D center - spanning architecture, chip design, software, and system engineering - we work closely with major US-based OEMs to deliver innovative, semi-custom silicon solutions. We are now extending our portfolio into AI acceleration, developing a next-generation NPU platform aimed at efficient, real-world AI deployment.
?Shape the Future of AI at the Silicon Level We are looking for a visionary Senior Technical Manager to build and lead our AI software stack for our next-generation NPU platform This is a rare opportunity to own the full software layer - from compiler infrastructure to Developer ecosystem - and make a lasting impact on how AI runs on silicon. What You'll Do; Build and lead a highly skilled AI software & algorithms engineering team, establishing engineering standards, development processes, and technical direction Define the end-to-end stack - compiler, runtime, Kernel libraries, and SDK - enabling efficient AI deployment on our NPU Drive AI compiler development using technologies like MLIR, TVM, LLVM or similar infrastructures to translate PyTorch/TensorFlow models into optimized NPU execution Champion model optimization - quantization, pruning, and hardware-aware techniques for maximum performance and power efficiency on the accelerator. Runtime, Drivers, and Firmware Integration - scheduling, memory management, and low-level software for AI workloads on-chip AI Kernel Libraries - Guide the development of highly optimized neural network Kernel libraries and performance-critical primitives tailored to the architecture of the NPU. Developer Ecosystem - Define and deliver the SDK, APIs, and development tools that allow internal teams and external developers to deploy AI models easily on the platform. Cross-Functional Architecture Collaboration - Work closely with silicon architecture and hardware design teams to ensure optimal hardware-software co-design, providing feedback on architecture, performance bottlenecks, and future ISA requirements.

Were expanding our Data & AI group and looking for a passionate, experienced Senior Data & AI Engineerto join our mission. This is a unique opportunity to work at the intersection of data engineering, LLMpowered systems, agentic workflows, and cybersecurity innovation

What youll work on
Data Infrastructure & EngineeringDesign, build, and scale production-grade data pipelines using Databricks, Spark, and modern cloud-nativetechnologies. Ensure high standards of data integrity, system performance, reliability, and scalability.
Core Backend & PlatformDesign and contribute to scalable backend services and platform capabilities using microservices andevent-driven architectures. Build reliable APIs, integrations, and asynchronous data flows that support highscale AI, data, and cybersecurity use cases.
LLM & Agentic SystemsDesign, prototype, and integrate LLM-powered systems, including Retrieval-Augmented Generationpipelines, agentic workflows, tool-using agents, multi-step reasoning flows, and AI-driven automation. Workwith technologies such as AWS Bedrock, OpenAI, Anthropic, LangGraph, vector databases, and modernorchestration frameworks.
AI-Assisted Engineering & Developer ProductivityExplore and apply advanced AI coding assistants and software-engineering agents, such as Codex andClaude Code, to improve development velocity, code quality, debugging, testing, and experimentation.Build proof-of-concepts and internal tools that help engineering and research teams work more effectivelywith AI-powered development workflows.
Intelligent Cybersecurity FeaturesCollaborate with Security Researchers, Engineers, and Product teams to identify opportunities forintelligent, data-driven features that deliver actionable cybersecurity insights to customers. Transformcomplex cybersecurity and platform data into reliable, explainable, and useful AI-powered capabilities.

We are looking for a Principal Software Engineer at the intersection of AI/ML and security. You will drive the architecture and delivery of autonomous agentic experiences that investigate, triage, remediate, and harden customer environments using LLMs, knowledge graphs, and the Security Graph (MSG).

This is a high-impact IC role reporting to the Exposure Management engineering leadership. You will influence strategy, mentor senior engineers, and ship production systems used by the largest enterprises in the world.

Responsibilities

Architect & Build Agentic Security Experiences
Design and implement Blue (investigate/triage), Green (remediate/harden), and Red (attack simulation) agents operating across customer environments.
Define agent architecture: planning, tool use (MCP skills), memory, context retrieval, and human-in-the-loop controls.
Build orchestration over the Security Graph, correlating exposure signals across cloud, device, identity, data, and AI.

Drive AI-Native Platform Design
Architect skill, knowledge, context, and memory layers for agentic security systems.
Design MCP-based skill interfaces for customization and extensibility.
Define how LLMs interact safely and accurately with structured security data (vulnerabilities, misconfigurations, attack paths, graph relationships).

Shape AI-for-Security Strategy
Partner with PMs and domain leads to define where AI autonomy vs. human involvement is needed.
Evaluate and integrate foundation models (Azure OpenAI, fine-tuned models) for tasks such as risk scoring, remediation planning, and blast radius analysis.
Stay ahead of industry solutions (Wiz AI-APP, CrowdStrike Charlotte AI, Palo Alto XSIAM).

Technical Leadership & Influence
Set technical direction across multiple teams (20-30 engineers).
Drive architecture decisions, design reviews, and engineering excellence.
Mentor senior engineers (L63-L65) and grow the AI-for-security discipline.
Represent the team across us (Security Copilot, MSG, Azure AI, Research).

We are looking for an ML Engineer to join a research-oriented group developing physics-informed neural networks for advanced sensing and optical measurement systems. The role focuses on training, validating, and improving neural network models that combine data-driven learning with physical modeling, simulation, and experimental measurements.

Responsibilities
Develop, train, and evaluate neural network models for physics-based sensing and reconstruction tasks.
Incorporate physical knowledge into ML models through data generation, model architecture, loss functions, constraints, or regularization.
Work with simulated and experimental datasets, including data. preprocessing, augmentation, validation, and error analysis.
Build robust training pipelines using Python and modern ML frameworks such as PyTorch.
Compare model predictions against ground-truth data from simulations, optical experiments, or measurement systems.
Collaborate with physicists and optical engineers to understand underlying physical models and translate them into ML workflows.
Analyze model performance, identify failure modes, and improve generalization from simulation to real-world data.
Design experiments to evaluate model robustness, sensitivity, uncertainty, and accuracy.

Power the Future with us! At SolarEdge (NASDAQ: SEDG), we're a global leader in smart energy technology, with over 3,000 employees, offices in 34 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. SolarEdge 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.
What you'll be doing in this position:
* Design and implement Smart Energy management solutions that connect smart devices using advanced and emerging protocols, ensuring exceptional performance, robust security, and seamless scalability.
* Develop and maintain high-quality code following best practices to ensure reliability, maintainability, and scalability.
* Work in a hardware-oriented environment, including integration with physical devices, troubleshooting complex setups, and validating software-hardware interactions
* Apply AI-driven tools and methodologies to accelerate development and enhance code quality.
* Work across multiple Embedded Linux platforms, contributing to complex system-level development and integration tasks.

Country:
Israel

City:
Herzliya

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

We are a global leader in high-performance smart energy technology, with over 3000 employees, offices in 34 countries, and millions of products installed in over 133 countries. Our diverse product offering comprises intelligent solar inverters, battery Storage, backup systems, EV charging, and complete home energy management ecosystems. By leveraging world-class engineering capabilities and with a relentless focus on innovation, we strive to create a world where clean, green energy from the sun is the primary source of power for our homes, businesses, and just about everywhere we thrive
The IoE group specializes in making our devices smarter and more connected. What You Will Be Doing:
* Develop and design high-quality code following best practices to ensure reliability, maintainability, and scalability.
* Optimize and enhance the performance of existing software components.
* Collaborate with hardware engineers to ensure seamless integration between hardware and software.
* Lead technical discussions, code reviews, and mentor junior engineers.
* Participate in the full software development life cycle including concept, design, development, deployment, and support.
* Leverage cutting-edge AI tools and the latest development features to accelerate development, improve code quality, and drive innovation across the team.
* On the Interface team, you'll develop the core infrastructure handling all communication between the device and external systems - cloud, mobile, and other on-site controllers - deployed across millions of devices worldwide.


Country:
Israel

City:
Herzliya

We are seeking an experienced Team Leader to lead a high-performing Full Stack Engineering team responsible for building scalable, performance-driven applications. This role combines hands-on technical expertise in Python with strong lea
You'll work on:
Lead and mentor a team of Full Stack Engineers, ensuring high-quality delivery and professional growth.
Remain hands-on with coding and architecture, primarily in Python, while guiding best practices.
Design and implement scalable, high-performance applications across backend and frontend layers.
Collaborate with Product, QA, and other engineering teams to deliver end-to-end solutions.
Drive technical decisions, code reviews, and architectural discussions.
Ensure adherence to SDLC best practices, CI/CD pipelines, and modern development workflows.
Promote a culture of ownership, responsibility, and continuous improvement within the team.
dership skills to guide and mentor a team of talented engineers.

In this role on our AI team, you'll focus on agentic workflow automation. You'll design, build, and deploy reliable AI agents that automate complex HR, payroll, and payment workflows, handling decision-making, document intelligence, and complex tasks that typically require human judgment.

What You'll Do:
Design and build agent-based systems that automate document processing, business insights, and complex enterprise workflows.
Build observability, evaluation, and feedback loops for agent behavior to improve reliability, accuracy, and trust in production.
Own the technical architecture and engineering standards for agentic systems.
Build or manage data pipelines to process large volumes of documents and unstructured data.
Collaborate with domain experts to identify high-value automation targets and deliver end-to-end solutions.
Stay current on agent frameworks, LLM capabilities and limitations, and apply emerging patterns pragmatically in production.