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We are looking for a highly experienced Senior Thermal Engineer to join our Architecture engineering team and take a key role in the development of next-generation SoCs, ECUs, and high-performance compute platforms for autonomous driving systems.
The position combines SoC/package thermal development, ECU cooling architecture, thermal simulation, characterization, validation, and vehicle-level thermal integration, working across multiple next-generation programs from early concept through qualification and production.
Please note: This position is also relevant for our other sites in Haifa, Petah Tikva, and Jerusalem.
What will your job look like?
Work on thermal development of next-generation SoCs and air/liquid-cooled ECU platforms, covering product requirements, thermal architecture, design, simulation, characterization, testing and qualification.
Perform detailed thermal performance assessment and CFD analysis of next-generation SoC/package designs, including die/package temperature distribution, heat spreading, thermal interfaces, material and stack-up optimization, and thermal resistance evaluation
Develop and evaluate advanced cooling solutions, including air cooling, liquid cooling, heat pipes, and advanced heat-spreading technologies.
Support vehicle-level cooling architecture and ECU integration for next-generation autonomous driving and Robotaxi platforms.
Define cooling requirements including coolant temperature, flow rate, pressure drop, thermal interfaces, and system thermal margins.
Correlate simulation results with laboratory and product measurements, drive thermal optimization and troubleshooting throughout development and qualification.
Work closely with silicon Arch, package, HW, mechanical, electrical, validation, suppliers, Tier-1s and OEM customers.

we are looking for a AI Engineer.
You will build the shared platform layer that makes agentic AI extensible, measurable, and self-improving. This is the foundation beneath everything: the orchestration engine, the skills registry, the evaluation harness, the guardrails system, the memory service, the integration gateway, and the tracing infrastructure - consumed by both the real-time conversational and offline video generation runtimes.
Your work is what separates it works for one customer with engineering involvement from it works for many customers across many domains without bespoke engineering per customer. You build the machinery once; customer-facing teams and eventually customers themselves extend it.

You will join a global DevOps & Platform team responsible for designing and operating distributed production systems at very high scale, with a relentless focus on quality, robustness, and reliability. We provide with the tools it needs to push forward product innovation and scale in the age of AI.
You will own projects end-to-end, drive new implementations forward, and act as a technical partner across the organization. Youll work closely with the Platform teams, Development teams, Architects, AI/ML Researchers, and Product, translating complex needs into resilient systems that scale.
Were looking for someone who takes ownership, who can see a problem or a need, shape the solution, and carry it all the way to production.

Delta Galil is a global, innovative apparel company operating across four continents and developing products for some of the world's leading fashion brands. At Delta Galil, people are at the heart of everything we do. We invest in personal and professional development, encourage innovation, and foster an empowering environment where individuals can grow, make an impact, and help shape the future. Ready to take your career to the next level? Join us! About the Role We are looking for an experienced Manufacturing Systems Specialist to play a key role in Delta Galil's digital transformation journey. In this position, you will lead the implementation, optimization, and continuous improvement of ERP and manufacturing systems that support our global production and supply chain operations. You will work closely with business stakeholders across manufacturing, planning, procurement, logistics, quality, and finance to drive process excellence, support large-scale transformation initiatives, and ensure operational efficiency across multiple manufacturing sites worldwide.
Key Responsibilities
* Analyze business processes and translate business needs into system requirements and solutions.
* Implement, configure, and optimize ERP and manufacturing systems to support operational excellence.
* Lead cross-functional implementation and process improvement projects across manufacturing and supply chain domains.
* Partner with business stakeholders to improve manufacturing, procurement, inventory, planning, and quality management processes.
* Support end users throughout the full project lifecycle, from requirements gathering and design through testing, go-live, training, and post-implementation support.
* Create business and functional specifications and documentation.
* Execute system testing and support User Acceptance Testing (UAT).
* Investigate business and system issues, perform root cause analysis, and recommend functional solutions.
* Work closely with software vendors, implementation partners, and internal development teams.
* Analyze operational data and provide insights to support data-driven decision-making.
* Ensure system stability, business continuity, and process effectiveness following implementation.
* Contribute to digital transformation and automation initiatives across Delta Galil's global manufacturing network.



Hybrid position:
Hybrid

Member of Technical Staff - Islo Engineering teams want background agents that pick up tasks, run on their own, and hand back real results - PRs, fixes, verified outcomes. Islo is the runtime for autonomous coding agents. We run agents in isolated environments connected to real tools with a policy layer that blocks what you didn't approve. Enterprise teams use us to deploy agents they can actually trust. We're a small team in Tel Aviv. Engineers figure out what to build, talk to customers directly, and ship it. We're growing fast and hiring people who want to own product - not just tickets. If you're ready to solve hard problems in a space that's being invented in real time, come join us. As a Member of Technical Staff You will engineer innovative cloud solutions: - Build robust, scalable cloud services in Rust, Python and TypeScript for Islo's agent runtime. - Design and implement secure, isolated agent environments using MicroVMs, virtualization, containers, and other isolation techniques. - Develop Developer -facing surfaces creating clean abstractions over low-level infrastructure. - Build agent orchestration, policy engines, and verification layers that let background agents pick up tasks, use real tools, and hand back results humans can review. - Build resilient, high-performance solutions. You will shape the product: - Own problems end-to-end - from understanding the user's pain to shipping the solution. - Talk to customers regularly: discovery calls, onboarding sessions, debugging their workflows, gathering feedback on what we shipped. - Turn messy, ambiguous requests into clear product decisions - what to build and what to cut. - Write lightweight specs and design docs when it helps the team move fast; skip the ceremony when it doesn't. - Prioritize the backlog based on customer impact and what the team learns in the field. - Demo new capabilities to customers and iterate based on what you learn in the room. - Join customer calls - technical deep-dives, onboarding, troubleshooting live agent runs. - Attend and speak at conferences and meetups on agents, Developer tools, and AI infrastructure. - Be the technical face of Islo with early adopters: answer hard questions, collect real-world failure modes, bring insights back to the team. We encourage you to apply even if your experience doesn't perfectly align with all requirements. We prioritize a positive attitude and potential over an exact match in experience or skills. Juniors are welcome - if you've shipped something, enjoy talking to users, and want to learn how autonomous agents actually run in production, we'd love to hear from you.

Landa seeks a Materials Researcher specializing in industrial inkjet ink formulations. The successful candidate will combine deep materials expertise with a practical understanding of complex Nanography system interactions, driving innovations from early research through manufacturing release.

Responsibilities:

* Development and optimization of water?based industrial inkjet ink formulations
* Design, plan, conduct, and analyze experimental work to support ink performance and reliability
* Maintain strong experimental traceability, documentation, and data integrity
* Collaborate with cross?functional teams including jetting, process, mechanical, service, and operations
* Provide technical solutions for customer escalations related to ink performance
* Support transfer of ink formulations from lab?scale development to pilot and production environments

Attributes:

* Self?motivated with strong ownership and execution mindset
* Team player with excellent communication skills
* Hands?on, practical approach to experimental work

Required Outstanding Graduate Algorithm Developer
About the team:
A global leader in autonomous vehicle (AV) technology, pioneering advanced driver-assistance systems (ADAS) and self-driving solutions.
Across the company, algorithm developers work at the forefront of AV/ADAS innovation - designing and implementing perception, mapping, computer vision, and decision-making algorithms, typically in Python or C++.
Algorithm developers join a variety of teams across a broad range of domains. This role serves as a central entry point, allowing us to match your expertise and aspirations with the team where you can make the greatest impact.
Algorithm developers contribute to diverse areas of innovation, including:
Detection: Developing algorithms to identify and track road users, lanes, and other key elements of the driving environment in real time.
Object Modeling: Developing algorithms to identify, classify, and measure objects (general, unclassified, etc.), enabling precise scene understanding.
Geometry: Developing algorithms to model road geometry, vehicle motion, and calibrations, providing essential spatial data that supports localization, 3D object placement, tracking, and other core perception tasks.
Mapping: Developing algorithms to create high-definition maps from large-scale, crowd-sourced data to enable precise localization and navigation.
3D Perception & Sensor Fusion: Designing algorithms for 3D reconstruction and multi-sensor reasoning to accurately model and understand the driving environment.
What will your job look like?
Your job will include a combination of algorithm development and programming in Python and C++
Work with image-based data, focusing on extracting and representing spatial information accurately and efficiently
Take initiative in identifying and solving complex algorithmic challenges in a fast-paced development environment
Collaborate closely with engineering and research teams in computer vision, data engineering, and related fields to deliver real-world solutions.

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

we are looking for a Senior AI Engineer - Exploration & Prototyping.
That is this role. You take an open question, run a focused spike, and come back with numbers and a recommendation. You read the source of the frameworks you evaluate rather than trusting their marketing. You build prototypes to settle arguments.
You do not own a subsystem and you do not ship to customers, which is exactly what protects the work: exploration inside a delivery team always loses to the sprint. You sit alongside the platform, research, and forward-deployed teams, you borrow their context freely, and your output is evidence they can act on.
You will be trusted with real influence early. The recommendations you write become the architecture other people build against, so the bar is not a working demo but a defensible conclusion, including the ones that say no.
What Youll Do:
Run technical spikes that close open decisions, covering agent orchestration frameworks, real-time transport, memory protocols, agent interoperability standards, LLM selection and routing, evaluation harnesses, and the production library and stack choices underneath all of it.
Build prototypes to de-risk, standing up something real quickly, proving or disproving the thing in question, and moving on without becoming attached to the code.
Read and evaluate unfamiliar codebases, going into the source of a candidate framework to find out whether it can actually support what we need rather than what its documentation implies.
Design the measurements that make a decision defensible, building the harness, running the comparison, and reporting latency, cost, and failure behavior honestly.
Own build-versus-adopt recommendations for platform infrastructure, frameworks, and libraries, including a clear statement of what it would cost to be wrong.
Write the recommendation down. Every spike ends in a short, decisive document another engineer can act on, with the evidence, the rejected options, and the reasoning behind the call
Hand off cleanly, transferring what you learned to the team that will own the capability in production, and staying available while they pick it up.
Track the landscape across agentic infrastructure, real-time frameworks, and adjacent AI tooling, and bring forward the things that genuinely change what we can build.

We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
What will your job look like:
Research and develop state-of-the-art computer vision and deep learning algorithms for ADAS and autonomous driving.
Participate in the entire development cycle, from initial research and prototyping to deployment on real-time embedded systems within the vehicle.
Collaborate with engineering and research teams in Computer Vision, Machine Learning, and Data Engineering to solve real-life problems.
Analyze large datasets to improve algorithm performance and robustness.

We are seeking a highly skilled and innovative Control Engineer to join our dynamic team dedicated to advancing the field of autonomous vehicles. As a Control Engineer, you will play a crucial role in designing, developing, implementing and testing hands on control algorithms to enhance the performance, safety, and efficiency of our autonomous vehicle systems.
What will your job look like:
Work on developing and optimizing control algorithms for the vehicle.
Run and analyze simulations to test autonomous vehicle in virtual environments.
Collaborate with hardware engineers to integrate control algorithms with the vehicle's hardware components, such as sensors, actuators, and onboard computers.
Working with communication protocols and interfaces for both internal and external communications with different components of the system.
Customer facing workshops to discuss and test your algorithms.
Testing your algorithms in an Autonomous vehicle.

Required Deep Learning Algorithm Engineer - REM Semantics
About the team:
You will be part of our REM (Road Experience Management) department which is responsible for the automatic High Definition map-making process, which is a key technology in our autonomous driving and high-end Driving Assistance systems.
You will be joining the team that builds the state-of-the-art AI-powered relevancy systems at scale. You will be designing and implementing semantic understanding engines that power data-driven products across autonomous driving and beyond, combining cutting-edge Computer Vision, Graph Neural Networks, and efficient inference to solve real-world perception challenges.
What will your job look like:
Conduct hands-on research and development of AI and Deep Learning algorithms for real-world automotive perception tasks.
Own projects end-to-end - from concept, through research, prototyping, designing, training, and evaluating neural network architectures, to integration and scalable deployment.
Analyze challenging edge cases and continuously improve model performance in complex driving scenarios.
Collaborate with algorithm developers, software engineers, product managers and system teams across the organization.
Work with large-scale datasets and real-world driving scenarios to improve model accuracy, robustness, and runtime efficiency.
Bring your ideas into production-ready systems that have a direct, measurable impact on autonomous vehicle technologies used worldwide.

Required Camera System Engineer
About the team:
We build camera-based ADAS and autonomous-driving systems with leading OEMs. This role is part of the Optical Path System Architecture and Integration team: the group that takes a new sensor integration from early requirements to a fully validated optical path.
As Camera System Engineer you will drive the full integration lifecycle of complex real-time embedded systems - bridging hardware platforms and software stacks from early requirements definition and platform bring-up through system-level validation and verification.
You will support pre-nomination and help close optical-path requirement gaps. Working closely with the Camera SW team and providing the pre-requisite they need for development and productization.
What will your job look like?
Define bring-up prerequisites and phases with architecture and program managers.
Support Bring up of optical path devices (Sensor, Serializer, Deserializer).
Review and contribute to Hardware-Software Interface specifications (register maps, memory maps, interrupts, boot sequences)
Support pre-nomination requirement definition, including customer-facing meetings when needed.
Support architecture with optical path feature requirements and sensors bring up requirements.
Support SW/HW integration test strategy including HIL setups and CI automated regression.
Deep co-debugging using Saleae, logic analyzers, and oscilloscopes; root cause analysis across hardware errata, timing, and firmware issues.

we are looking for a Pre-Sales Solution Engineer.
You are a solution-oriented sales professional with expertise in presales, software development, and crafting business solutions. A process-driven builder, you thrive on exploring solution development methodologies to deliver optimal results for clients.
You will:
Operate consultative with prospects and existing customers to define their challenges and opportunities. Map these challenges to the ecosystem by presenting differentiating and sustainable business value.
Full ownership to the success of customer PoC/Pilots through effective management of acceptance criteria and issue escalation/resolution. Run Security Questionnaires with prospects, and master the ability to demo vendor risk assessments.
Educate and become a trusted advisor and challenge assumptions and current status while delivering value to prospects and customers.
Present art of the possible and think outside the box approaches to implement privacy solutions.
Support technical and business discovery activities including workshops, and demonstrations, across multiple opportunities
Work closely with the sales team on account strategy and identifying additional opportunities in existing and new accounts.
Develop and deliver exceptional and engaging company/product presentations and demonstrations.
Work with all technical levels.
Be the technical product expert and advisor for customers and stay up-to-date on the data solutions competitive landscape.
Partner with Product Management and Engineering to provide feedback from the field and represent the customer perspective.
Identify and write internal and external technical collateral, like typical deployment architectures or best practices and industry standards.
Collaborate with the marketing team to generate demos, case studies, blogs, and videos.
Maintain a knowledge hub or repository of best practices, resources, and insights (API docs, code examples).

We are looking for an Applied AI Engineer to join the MECI Interfaces team within the Software Engineering organization. The MECI Group enables our algorithmic development flow by building scalable CI, build, test, and AI-driven tooling that supports the full development lifecycle. Our platforms allow us to scale efficiently and increase development velocity, while maintaining high standards of reliability, collaboration, and developer well-being.
As an Applied AI Engineer, you will be at the forefront of integrating Large Language Models (LLMs) and agentic workflows into our internal platforms. Your primary goal will be to solve complex problems across the Software Development Life Cycle (SDLC) by building intuitive, AI-powered tools that directly support our developers and internal users. This role offers the unique opportunity to both expand the intelligence of our existing developer tools and architect entirely new workflows from the ground up in a highly technical, fast-paced environment.
What will your job look like?
Design, develop, and deploy AI-driven internal tools and agentic workflows that accelerate the SDLC and reduce friction for our developers.
Expand the capabilities of existing platforms by embedding smart, context-aware LLM features.
Identify high-impact bottlenecks across the engineering organization and build zero-to-one AI solutions to solve them.
Architect robust orchestration layers around LLMs, focusing on practical implementations of custom system "skills," tool calling, Model Context Protocol (MCP) integrations, memory management, and Retrieval-Augmented Generation (RAG).
Maintain a framework-agnostic approach, rapidly evaluating and adopting the most effective AI models, APIs, and open-source techniques as the landscape evolves.