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Requirements:
* Bachelor’s degree in Computer Science, Software Engineering, or related field.
* At least 3 years of experience in software development.
* Proficiency in programming languages such as C++, Python, or Java.
* Strong understanding of software development life cycle and methodologies.
* Experience with software version control systems (e.g., Git).
* Ability to work effectively in a collaborative team environment.
* Excellent problem-solving skills and attention to detail.

Requirements:
Bachelor's degree in Computer Science, software engineering, electronics or an exact scientific field - required
Proven experience in development in Hard Real-Time systems - required Experience working with hardware components, interfaces and communication protocols - a significant advantage.
Experience in development, integration and testing of Real-Time Embedded systems - an advantage.
Ability to lead independent development of a system from defining needs to final testing and implementation at the customer - an advantage. Experience in writing development documents (specifications, planning, testing) - an advantage.

Requirements:
Requirements:
* Mechanical Practical Engineer / Mechanical Engineer - Mandatory
* Deep technical understanding of machining processes
* Proven experience in CNC programming - 3 years and above
* Good knowledge of FANUC, SIEMENS controllers
* Experience with CIMATRON, SOLIDCAM, NX software
* Mastery of technical English
* Self-disciplined and high personal responsibility
* Team player
* Good interpersonal skills. Excellent interpersonal communication
* Highly motivated and willing to work hard, including overtime

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:
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.