Decoding Researcher jobs in Israel

What you’ll be doing:

• Be involved in offensive security researcher on a wide range of products.

• Assist with defining and making sure software development processes meet security and coding standards.

• Perform security threat modeling for NVIDIA Networking products.

• Design and make security architecture recommendations to satisfy security guidelines and requirements.

• Mentor teams and developers, promoting guidelines on the best security practices.

• Be a technical focal point across multiple development teams and provide hands-on security engineering expertise.

What we need to see:

• Academic degree in computer science, electrical engineering, or related field. Candidates with equivalent work experience will also be considered.

• Demonstrated experience of 5+ years in security research.

• Familiarity with applied cryptography, threat modeling, common attack vectors and mitigation techniques.

• Ability to work independently, and collaboratively in a constantly evolving environment.

• Excellent communication and interpersonal skills.

Ways to stand out from the crowd:

• M.Sc. or PhD in computer science, electrical engineering, or related technical field.

• Familiarity with the cloud environment security ecosystem.

• Experience with high-scale deployment challenges.

• Demonstrated security research experience and publications.

• Conduct research on hardware security vulnerabilities, threat models, and potential mitigations.
• Analyze and evaluate hardware architectures for potential security weaknesses, including ASICs, System-on-Chip devices, microcontrollers, memory devices, etc.
• Develop proof-of-concepts to demonstrate hardware vulnerabilities or mitigations.
• Collaborate with multi-functional teams (architecture, design, verification, firmware, etc.) to assess and improve hardware security mechanisms.
• Explore groundbreaking security topics, such as side-channel attacks, fault injections, and post-quantum security implications for hardware.

• Currently pursuing a B.Sc./M.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Shown understanding of computer architecture and hardware design principles.
• Basic knowledge of security concepts (e.g., cryptography, secure boot, trusted execution environments).
• Familiarity with programming languages such as C/C++ or Python.
• Strong analytical and problem-solving skills with the ability to work independently and in a team.
• Good interpersonal skills and ability to document research findings clearly.

• Hands-on experience with hardware security topics (e.g., side-channel analysis, fault injection, hardware reverse engineering).
• Familiarity with RTL design and verification (Verilog/ SystemVerilog).
• Experience using hardware development tools (oscilloscopes, logic analyzers, evaluation boards).
• Contributions to security-related open-source projects, research papers, or participation in Capture-The-Flag (CTF) competitions.
• Knowledge of emerging hardware security standards and technologies - Caliptra, Post-quantum cryptography, Physical Unclonable Function, etc.

What you'll be doing:

• Research, invent, and implement groundbreaking algorithms for LLM inference to advance the state of the art in both low-latency and high-throughput scenarios.
• Translate research into practical software solutions that directly impact NVIDIA's products and customers.
• Collaborate with internal research, engineering, and product teams across the globe to drive the development of sophisticated inference technologies.
• Analyze the performance of new algorithms on NVIDIA’s latest hardware, identifying bottlenecks and opportunities for algorithmic optimizations.
• Partner with leading scientific organizations and industry pioneers to remain at the forefront of technological advancements and integrate the latest innovations into practical applications.

What we need to see:

• MSc/PhD in Computer Science, Electrical Engineering, or a closely related field.
• At least 3 years of proven experience in deep learning research or applied research.
• At least one publication in a top-tier AI/ML conference (e.g., NeurIPS, ICLR, ICML).
• Deep understanding of LLM architectures coupled with hands-on experience in training large-scale models.
• Excellent programming skills, particularly in Python and deep learning frameworks like PyTorch, and experience with software engineering best practices.
• A strong problem-solving mentality and a proactive demeanor, driven by the ambition to deliver solutions with real-world impact.

Ways to stand out from the crowd:

• Hands-on research experience in LLM inference optimization algorithms such as speculative decoding or parallelization strategies.
• Proven experience with High-Performance Computing (HPC) environments, including training or running inference on large-scale GPU clusters (tens to hundreds of GPUs).
• Deep familiarity and experience with popular LLM inference systems (e.g., vLLM, TensorRT-LLM).
• Experience from a world-class industrial research group or a top-tier institution.