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Requirements:
Requirements:
Education B Sc. in: Electrical Engineering or Physics. At least 2 years' experience in reliability / testing lab. Experience with electronic TEST equipment (DMMs, LCR, DAQ, Scope etc.) Ability and willingness for hands-on assignments. Advantage to: Electrician certificate. Experience in board design. Experience in Failure Analysis. Familiar with: JEDEC, AEC, IEC and JEITA standards. Additional Skills: Good Engineering skills. Good Personal skills. Self-motivated and organized. Strong problem-solving skills and analytical ability. Good written communication in both Hebrew & English.

Requirements:
* 2-3 experience working with the Elastic Stack
* Strong experience building dashboards, monitoring screens, and visualizations using Kibana
* Experience in data modeling, normalization, and parsing in alignment with the Elastic Common Schema (ECS)
* Hands-on experience developing and implementing monitoring rules / detections based on the ECS data model
* Experience with Elastic Security , including customization, extensions, and implementation across Security Domains / Detection & Response
* Advantage: experience working with data integrations and collaborating directly with clients High security clearance is a plus

Requirements:
* B.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
* 6+ years of experience in Embedded systems / firmware development.
* Strong experience in low-level programming ( C / C ++) and system -level understanding.
* Hands-on experience working with Linux in Embedded environments.
* Proven ability to work across hardware and software interfaces ( system integration).
* Strong system -level thinking and architecture understanding.
* Ability to work independently and take full ownership of a domain.
* Experience or familiarity with Lua- Advantage

Requirements:
What we need to see:

B.SC./ M.SC. in Electrical Engineering/Computer Engineering (or equivalent experience).

You should have at least 5+ years of hands-on Full-chip layout and Physical Verification experience, demonstrating your proven expertise.

A strong background in Physical Verification methodology, including DRC / LVS / ANT / ERC / DFM in advanced process nodes is necessary.

Proficiency using Python, Tcl, Shell, Make scripting.

Experience in Linux environments.

AI tools orientation or alternatively a desire to learn.

Familiarity with physical build EDA tools, including Synopsys (ICC2/FC) and Cadence (Innovus).

Familiarity with Physical Verification tools: Synopsys (ICV), Siemens (Calibre)

Self-motivation, attention to detail, and good interpersonal skills.


Ways to stand out from the crowd:

Experience with data collection and analysis

Experience in methodology definition / flow owner of Full-chip / Place and Route

Great teammate.

Ownership, self-learning skills, and ability to work autonomously.

Requirements:
What we need to see:

Hold a M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university (or equivalent experience).

5+ years of industry experience (or equivalent) in software architecture, hands-on development, AI/ML, applied research, or related fields.

Strong background in software or solution architecture, applied AI/ML research, or hands-on development of production-grade AI systems.

Industry experience building and shipping AI-powered tools or ML pipelines (not just training models - end-to-end delivery).

Strong understanding of LLM capabilities and limitations - prompt engineering, fine-tuning, RAG, agent architectures.

Experience with at least two of: reinforcement learning, classical ML, NLP/information retrieval, evaluation framework design.

Strong understanding of AI development and evaluation pipelines.

Can reason about trade-offs: when to use which approach, with real reasoning backed by shipping experience.

Strong programming skills (Python required; familiarity with ML frameworks - PyTorch, HuggingFace, etc.).

Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.

Ways to stand out from the crowd:

Experience with LLM-based code generation, code review, or developer tooling.

Familiarity with eval frameworks and feedback loop design (online and offline evaluation).

Experience with AI agent orchestration (multi-agent systems, tool use, planning).

Shown research track record (publications, open-source contributions).

Knowledge of AI-assisted development tools and their underlying architectures.

Requirements:
What we need to see:

B.Sc./M.Sc. in Computer Science, Computer Engineering, or a related technical field.

8+ years of software engineering experience building production distributed systems.

Core Systems Programming: Expert-level proficiency in languages such as Go, C++, or Rust, with a focus on high-performance, concurrent architectures.

Solid understanding of Kubernetes and container-based deployments for production services.

Experience deploying, monitoring, and maintaining ML models or data-intensive services in a production environment.

Comfort working in ambiguous, fast-moving environments where the product is still being shaped.


Ways to stand out from the crowd:

Experience building ML model-serving platforms or MLOps tooling (model registries, A/B rollout frameworks, feature stores) at scale.

A track record of taking systems from prototype to stable, production-grade platform serving real enterprise customers.

A "Systems" Thinker: You don't just write software; you understand the full stack, from how data moves across the wire to how its processed in a distributed cluster.

Practical Innovation: The ability to simplify complex problems and build internal tools or frameworks that empower other engineering teams to move faster.

Requirements:
What we need to see:

B.Sc. or M.Sc. in Computer Science, Computer Engineering, Electrical Engineering, Industrial Engineering, or equivalent experience.

15+ overall years of relevant professional experience in software engineering organizations, engineering operations, DevOps, integration, technical program management, process management, or system software execution roles.

Minimum of 7 years managing R&D engineers.

Proven people leadership experience, including leading teams, mentoring managers or senior engineers, setting direction, and building an operational or engineering productivity function.

Strong technical understanding of complex software systems, Linux environments, infrastructure software, integration flows, release processes, and system-level debugging.

Experience improving engineering workflows such as integration, release readiness, CI/CD, issue handling, requirements flow, secure development, vulnerability handling, or inter-team handoffs.

Excellent communication and cross-functional leadership skills, with the ability to align engineering leaders and turn ambiguous operational, technical, or usability problems into clear actions and priorities.

Ways to stand out from the crowd:

Familiarity with DOCA, BlueField DPUs, SmartNICs, cloud infrastructure, developer frameworks, data center infrastructure, or large-scale system software.

Experience leading DevOps, integration, lab, release, engineering productivity, security process, or UX/usability functions in a complex R&D organization.

Proven success improving out-of-box product experience, provisioning, deployment workflows, documentation quality, automation, or customer-facing integration flows.

Requirements:
What we need to see:

Bachelors in Computer Science, Software Engineering, Data Science, or a related field, or equivalent experience.

8+ years of experience as an AI solutions engineer, machine learning engineer, or software engineer building production AI/data solutions.

Strong experience designing, developing, deploying, and maintaining end-to-end AI applications in production.

Hands-on expertise with Python and modern software engineering practices.

Practical experience with LLMs, AI agents, RAG, workflow orchestration, and data/analytics applications.

Strong background building data pipelines, APIs, services, and applications on top of structured and semi-structured engineering data.

Strong communication skills and a proactive, ownership-driven mindset.

Advantage: experience in semiconductor, hardware, product engineering, test, characterization, or manufacturing analytics environments.


Ways to stand out from the crowd:

Experience building AI solutions for engineering or manufacturing organizations.

Familiarity with agent frameworks, vector databases, telemetry platforms, or internal knowledge/data systems.

Background in cross-functional work spanning software, data, infrastructure, and product engineering.

Proven track record of introducing new technical capabilities and driving adoption across engineering teams.

Requirements:
What we need to see:

B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field.

5+ years of software engineering experience, preferably in system software, infrastructure, validation, or performance-focused environments.

Strong programming skills in Python and at least one system-level language such as C/C++.

Experience developing automation and test infrastructure for complex hardware/software systems.

Hands-on experience running, debugging, or optimizing AI, HPC, or large-scale system workloads.

Good understanding of system-level architecture, including interactions across hardware, firmware, drivers, operating systems, and application layers

Experience working in Linux environments and with scripting, telemetry, logging, and data analysis tools.

Strong debugging and problem-solving skills, with the ability to work across multiple engineering disciplines.

Good communication skills and the ability to drive technical work in a fast-paced, cross-functional environment.

Ways to stand out from the crowd:

Experience with our platforms, GPU systems, or rack-scale AI infrastructure.

Background in power, thermal, performance, or storage/drive characterization.

Experience with workload automation, cluster orchestration, or lab infrastructure.

Familiarity with AI benchmarks, training/inference workloads, and system stress methodologies.

Experience in post-silicon validation, production testing, or system bring-up.

Requirements:
What we need to see:

BSc in Electrical Engineering or Computer Science (or equivalent experience).

5 + years of proven experience writing enterprise software.

Strong C and Python coding skills.

Previous experience with I2C, PSUs, SMBus, PHY Layer technologies and doing hardware bringups.

Good knowledge of Linux systems administration, Linux internals and tools.

Experience using source code management tools, as well as code coverage, unit testing and debugging tools.

Excellent written and verbal communication and interpersonal skills.

Able to work independently with minimal direction.


Ways to stand out from the crowd:

Strong background in Linux systems and Linux kernel networking.

Strong background in debugging kernel and hardware issues.

Familiarity with Data Center Networking technologies.

Exposure to CI/CD tools.

Requirements:
What we need to see:

B.Sc. degree in Computer Science or equivalent experience.

3+ overall years of experience in technical software development.

Experience in C++ and Python programming on top of Linux operation system.

Fast and self learner with outstanding communication and technical skills.

Motivated, responsive, and keen on process improvement.


Ways to stand out from the crowd:

Experienced in software development on open source project.

Experienced in Networking protocols: L2 and L3.

Background in Linux shell scripting.

Scrum methodology and active scrum master.

Requirements:
What we need to see:
B.SC./ M.SC. in Computer Engineering/Electrical Engineering/Communication Engineering.
5+ years of validated experience in ASIC Verification.
High Level of English.

Ways to stand out from the crowd:
Background in Specman.
Knowledge in HDL (Verilog/VHDL).
Knowledge in Mixed Signals, Analog, and Behavioral Models for Verification.
Knowledge in Chip boot and Infrastructures.