דרושים » אבטחת מידע וסייבר » Senior AI Security Researcher

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.

we are seeking an experienced and visionary Head of Research to lead, shape, and advance the future of AI innovation across the organization. In this role, you will own the research strategy end-to-end - from long-term roadmap design to hands-on exploration, and guide a multidisciplinary team of NLP research engineers and linguists toward breakthroughs that elevate our core medical coding engine.

You will play a key role in the company, balancing exploratory research with high-impact product delivery. You will partner with Product, Engineering, and executive stakeholders to identify strategic opportunities, drive prioritization, and translate research capabilities into real-world outcomes at scale.

Responsibilities:

Manage and mentor a multidisciplinary research team while driving both technical excellence and personal growth.
Define the long-term research roadmap aligned with product and business objectives.
Lead the full research lifecycle, from ideation and feasibility studies to experimentation, evaluation methods, and production-ready delivery.
Evaluate and introduce new research capabilities and emerging trends such as LLM-based reasoning, semantic/graph modeling, hybrid rule-learning, and other frontier techniques.
Continuously track scientific trends to maintain a state-of-the-art research practice.
Collaborate closely with Product and Engineering teams to translate domain challenges into algorithmic solutions with measurable product impact.
Represent the Research function at leadership forums, communicate priorities and outcomes, and align stakeholders around research strategies and milestones.

we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of Machine Learning, GenAI, and computer vision within the automotive sector.
With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply Embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.
We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of UVeyes inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges.
A day in the life and how youll make an impact:
* Design and Development of novel, robust and efficient Machine Learning / Deep Learning algorithms for major Vision challenges.
* Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems.
* Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data -centric AI methodologies (active learning, data curation).
* Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for Real-Time inference constraints (on Edge/Cloud devices).

We are looking for a visionary AI Lead to build our internal AI platform and architect adaptive intelligence systems that serve as a dedicated security architect for each of our customers. You will lead a team of AI Researchers and Engineers to move beyond simple integrations and build true autonomous security solutions.
What You Will Build
Autonomous Workflows: Build agents that execute security workflows end-to-end, automating detection, investigation, and response processes.
Runtime Defense: Productize research into active runtime guardrails and defensive control mechanisms.
Internal AI Platform: Build the shared infrastructure for models, training, and evaluations to enable safe, scalable AI features across the organization.
Adaptive Intelligence: Oversee the development of models that learn from customer-specific environments to generate high-signal, personalized insights.
Responsibilities
Lead the AI Research Group, managing AI Researchers, Engineers, and DevOps.
Own the intelligence engine end-to-end, delivering next-generation analytics and contextual visualization features.
Drive the strategic "build vs. partner vs. buy" decisions for cloud prevention and AI controls.
Collaborate with the Threat Team to develop AI-driven threat detections against emerging attack vectors and novel AI threats.

we are looking for a Data science Team Lead.
As the Data Science Team Lead, you will lead a talented team of data scientists and ML engineers building the infrastructure, systems, and workflows for designing, training, evaluating, and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.
This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving, customer-specific model tuning, offline AI evaluations, and scalable ML systems in a production-grade SaaS environment.
If you are passionate about applied machine learning, fraud detection, and building intelligent systems at scale - we want you on our team.
What youl do:
Lead and mentor a team of Data Scientists and ML Engineers focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.

We are seeking a hands-on Applied AI Scientist to join our core R&D team and drive the development of next-generation AI systems for autonomous driving. This role sits at the intersection of applied research and deployment - you will go from reading papers to shipping production systems. You will work directly on our multi-layered autonomy architecture, with a primary focus on real-time predictive models for driving decisions.
A deep technical role for someone who thrives on turning cutting-edge research into real, working systems under hard constraints.
Responsibilities:
Own the research-to-deployment cycle for predictive driving models - from literature review and prototyping through to production integration
Design, implement, and iterate on real-time predictive models, including vision-language models, motion prediction models, and inverse reinforcement learning approaches (e.g., imitation learning, reward recovery)
Collaborate on higher-level reasoning systems, contributing to vision-language-action models that handle complex edge cases and long-horizon planning
Bridge cloud-scale training with edge deployment - work on model compression, quantization, speculative decoding, and efficient inference for embedded automotive platforms
Evaluate and integrate state-of-the-art techniques from the broader AI research community into our autonomy stack
Collaborate closely with internal R&D teams to unblock technical challenges, accelerate delivery, and raise the overall technical bar.

Are you an innovative security researcher with a deep understanding of the cyber threat landscape and a passion for protecting modern environments? Do you want to tackle the challenge of securing enterprise networks against evolving threats?
We are seeking a highly skilled professional to focus on the critical, fast-paced domain of Virtualization Security. As a foundational member of a newly formed and growing team, you will explore the 'blue ocean' of threat detection, pioneering next-generation capabilities within the worlds largest cybersecurity enterprise. This is a unique opportunity to apply your expertise and influence the future of threat prevention-helping us build cutting-edge security solutions from the ground up.
Key Responsibilities
Conduct deep research into virtualization technologies, and targeted attacks to fortify our attack prevention mechanisms.
Stay current with the latest attacker methodologies, APT campaigns, and Tactics, Techniques, and Procedures (TTPs) targeting virtualization systems.
Analyze emerging threats and malware to identify new techniques and formulate effective detection and prevention strategies.
Leverage AI and big data methodologies to investigate and analyze extensive datasets across our customer base.
Design cutting-edge protection components and develop sophisticated detection rules to enhance the effectiveness of our security solutions.
Drive the research and development of novel protection concepts, seeing them through to production-grade quality, and serve as a subject matter expert in the field.
Play a pivotal role in shaping the future of our security product offerings.
Collaborate closely with Engineering, Product Management, and other research teams to seamlessly translate research findings and insights into new production features.

We are looking for a Research Team Lead to establish and lead a cross-product research team focused on horizontal, high-impact initiatives that influence multiple offerings.
Unlike product-embedded research roles, this team drives foundational and strategic research projects across networking, security, identity, automation, and AI-driven capabilities. Examples include large-scale reasoning systems, autonomous policy frameworks, cross-domain detection and response concepts (xOps), and platform-wide intelligence capabilities.
You will combine deep technical expertise with strong leadership and execution skills -identifying impactful research directions, building a high-performing team, and turning advanced research into real platform capabilities used by thousands of customers worldwide.
Responsibilities
Technical Vision & Strategy:
Define and execute the roadmap for cross-product research initiatives.
Identify high-leverage research opportunities that impact multiple domains and products.
Drive long-term architectural thinking and influence platform evolution.
Balance innovation, experimentation, and production-readiness.
Team Leadership:
Recruit, mentor, and grow a multidisciplinary team of researchers (AI, data, algorithms, networking, security).
Establish high standards for research rigor, experimentation methodology, and engineering quality.
Foster a culture of ownership, collaboration, and technical excellence.
Research & Execution:
Lead complex, ambiguous research initiatives from ideation through validation and productionization.
Design large-scale experiments and validation methodologies using our data platform.
Drive innovation in areas such as:
Autonomous policy systems
Cross-domain detection and response frameworks
Large-scale reasoning and decision systems
Data-driven optimization and automation capabilities
Ensure research outcomes are measurable, scalable, and aligned with business impact.
Cross-Functional Collaboration:
Work closely with Product, Engineering, Architecture, and Product Research teams to translate research into shipped capabilities.
Provide technical guidance and influence cross-organizational decisions.
Act as a bridge between exploratory research and production systems.
Communication & Influence:
Present research findings and strategic recommendations to senior leadership.
Produce clear technical documentation, design proposals, and internal position papers.
Represent Platform Research as a center of excellence for cross-product innovation.

We are looking for an exceptional Senior AI Researcher to join our fast-growing company during a pivotal stage of market expansion. In this role, you'll lead groundbreaking research in SOC automation, develop industry-defining benchmarks, create innovative prototypes that transform into product features, and establish thought leadership through conferences and publications. If you're passionate about revolutionizing security operations through AI and excited about shaping industry standards, we'd love to hear from you!
What Will You Do?
Lead research initiatives that redefine SOC automation capabilities, creating industry benchmarks and evaluation frameworks for AI in security operations
Design and develop functional prototypes that demonstrate breakthrough concepts, transitioning research into product features with engineering teams
Collaborate with security researchers, Product Marketing, and the Head of AI to analyze competitors and align research priorities with commercial objectives
Present findings at premier conferences (BlackHat, RSA) and publish tools/content that advance security automation and establish thought leadership
Mentor engineering teams on advanced AI techniques and their practical applications in security contexts

we are looking for a Senior Machine Learning Engineer I.
As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.
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