דרושים » אבטחת מידע וסייבר » Research Engineer

we are looking for a Senior Software Engineer.
As a Software Engineer , you will take ownership of designing, building, and scaling the production systems that power our evaluation and security platform for frontier AI models.
Your work will focus on creating robust, resilient, and high-performance infrastructure-whether thats distributed pipelines, backend services, or tooling that supports our research teams.
This role is engineering-first with a strong research and cyber component. You will develop systems that must run reliably in production, integrate with external partners, and support large-scale data, experiments, and automated evaluations. Youll drive architectural decisions, lead technical implementations, and shape how our platform evolves.
Representative Responsibilities:
Architecting and scaling production-grade systems and workflows.
Building backend services, APIs, and monitoring tools for large-scale model evaluations.
Designing infrastructure that supports research experiments at scale.
Implementing agent frameworks in production environments
Designing and building challenges that measure a models ability to evade discovery, allowing us to see if models can operate on remote systems while avoiding detection by common defensive security tools.

we are looking for a AI Researcher.
As an AI researcher, you'll be at the forefront of researching advanced frontier model capabilities and agent behavior, and help shape the future of AI security evaluation and mitigation. In this role, you will advance the frontier knowledge of AI and agentic frameworks, methods of assessing their ability, and mitigations for dangerous capabilities.
Representative projects:
Researching capability elicitation methods to enhance model performance in evaluations.
Researching methodologies to assess generalization and coverage in model capabilities evaluation frameworks.
Contributing to academic publications and delivering research findings to customers.
Creating unique solutions to mitigate scenarios of AI loss of control or misalignment.
Advising and supporting the development of the products were building.

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
Your Impact & 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 looking for a Cyber Researcher.
As a cyber researcher , you will be at the forefront of research on AI security. You will engage with questions such as how to protect the weights of an advanced model against cyber threats, and how to evaluate cyber capabilities such as AIs ability to exploit vulnerabilities, carry out network attacks, and develop malware. This role sits at a unique intersection of cybersecurity expertise and AI capabilities, where your background in vulnerability and security research will help shape the future of AI security.
Representative projects:
Expanding the quantity, quality, and variety of our cyber capabilities evaluation challenges (e.g. constructing original CTF-style vulnerability & exploitation challenges, network attack simulation challenges, and more, including original types of challenges).
Leading research into methods to mitigate cybersecurity risks related to the misuse of AI, the theft of model weights, or risks associated with integrating models with dangerous capabilities in AI agents.
Publishing your research and/or delivering research to our customers.
Advising and supporting the development of the products were building.

We're looking for an AI researcher to take an integral part in research into how these models behave, how they should be evaluated, and how they can be deployed and used more efficiently across real engineering workloads.
This is a deeply technical research role with direct product impact.
You'll study frontier and open-source models, develop evaluation frameworks, investigate inference and model optimization techniques, explore local deployment strategies, and help answer questions such as:
Which model should handle a particular task?
How much capability do we lose when we quantize it?
Can a smaller local model replace a frontier API for a specific workload?
How should models be routed across latency, cost, privacy, and quality constraints?
How do we measure whether one model is actually better than another for agentic software engineering?
Your work will directly shape model strategy and the intelligence behind our AI infrastructure products.

we are a leading trust, safety, and security company. Just like Alice herself, we go down the rabbit hole into the emerging world of AI and focus on safeguarding these technologies. In a world where AI has fundamentally changed the nature of risk, our company offers coverage across the entire AI lifecycle. We're currently on the ground floor of an exciting new initiative: building an "Elite Collective" of the world's premier cyber specialists-high-stakes, project-based work for the "best of the best" red-teamers in the industry. Work is on-demand and project-dependent, scaling up and down based on the needs of the client. This is not a high-volume, repetitive role; it is an opportunity to be tapped for specific, high-impact interventions when your unique expertise is required. The most sophisticated technology challenges in the world are waiting down the rabbit hole. Were looking for the sharpest minds to help us secure the frontier. The invitation is open: Come join us at the tea party. About the position: As one of our companys Security Red Team Specialists, youll focus on Generative AI Models. You will play a critical role in enhancing the security and integrity of our cutting-edge AI technologies. Your primary responsibility will be to conduct analysis and testing of our generative AI systems, including but not limited to language models, image generation models, and any related infrastructure. Your objective is to help clients secure their AI models and frameworks by identifying weaknesses, assessing risks, and providing clear steps for improvement. Key Responsibilities
* Simulated Cyber Attacks: Conduct sophisticated and comprehensive simulated attacks on generative AI models and their operating environments to uncover vulnerabilities.
* Vulnerability Assessment: Evaluate the security posture of AI models and infrastructure, identifying weaknesses and potential threats.
* Risk Analysis: Perform thorough risk analysis to determine the impact of identified vulnerabilities and prioritize mitigation efforts.
* Mitigation Strategies: Collaborate with development and security teams to develop effective strategies to mitigate identified risks and enhance model resilience.
* Research and Innovation: Stay abreast of the latest trends and developments in AI security, ethical hacking, and cyber threats. Apply innovative testing methodologies to ensure cutting-edge security practices.
* Documentation and Reporting: Maintain detailed documentation of all red team activities, findings, and recommendations. Prepare and present reports to senior management and relevant stakeholders.
About us:
we are a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, our company provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. we are widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.
This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

Were looking for a passionate Lead or Senior Offensive Security Engineer for our growing Offensive Security Automation team. This hands-on offensive security position requires a cyber security professional whose primary focus is to perform security assessments and vulnerability research using internal AI tools using frontier models, with a focus of designing and developing the AI automation and autonomous harnesses together with the team.

This is a role for someone who can perform offensive security testing at scale, combining deep security expertise with the judgment to direct and improve AI-driven tooling.

What You'll Actually Be Doing
Perform security assessments and vulnerability research across web applications, APIs, and cloud/hybrid infrastructure, using internal AI tools and frontier models to scale coverage and depth that you will develop.
Make sure our internal solution can perform exploitation, vulnerability chaining, business logic and authorization abuse, privilege escalation, and lateral movement, beyond what automated tooling alone can find.
Run end-to-end engagements: scoping, execution, reporting, and remediation guidance.
Discover systemic/architectural weaknesses, not just isolated bugs, and drive secure-by-default fixes.
Partner with engineering, security architecture, and detection & response teams to close root causes and validate control effectiveness.
Produce high-quality technical reports with clear exploitation paths and prioritized remediation.
Develop the automation and autonomous harnesses that direct frontier models to perform offensive security testing continuously and at scale.
Design agent-based workflows that reason over large data, plan for risk signals, business logic and execute multi-step offensive testing that will adapt based on results, recon, hypothesis ranking, chaining of bugs exploitation, AI-Driven assessments, and reporting.
Establish human-in-the-loop checkpoints so automation scales offensive coverage without sacrificing safety or precision.
Translate your own tradecraft into reusable, explainable automation that the team can run and build on.

As Security Research Team Lead at our company, you will lead the team turning security research and enterprise security data into actionable insights and product capabilities. You will combine people management with hands-on technical leadership, helping customers understand their exposure and get more value from their security tools.
Were looking for a leader with a strong background in cybersecurity research, deep understanding of enterprise security tools, and a data-driven approach to solving problems. You should be equally comfortable mentoring researchers, shaping a research roadmap, and joining customer calls to explain findings and understand real-world challenges.
What You'll Do
Lead and Develop the Team: Manage, mentor, and grow a team of security researchers. Set clear goals, provide technical guidance and feedback, and build a culture of rigor, curiosity, and ownership.
Own the Research Roadmap: Define and prioritize research initiatives in partnership with product and engineering. Balance customer needs, emerging threats, and strategic opportunities, taking projects from initial investigation through production delivery.
Drive Security Tool Research: Lead deep research into enterprise security platforms, including EDR, SIEM, firewalls, IAM, and vulnerability management tools. Assess configurations, policies, coverage, and defensive capabilities to identify gaps and improve security effectiveness.
Engage Directly with Customers: Lead technical customer discussions, explain findings clearly, investigate complex questions, and turn feedback into research and product improvements.
Turn Data into Security Insights: Guide how the team collects, models, correlates, and validates security data. Translate fragmented telemetry and configuration data into reliable assessments, prioritized findings, and actionable recommendations.
Shape Integrations and Product Capabilities: Own the research requirements and security logic behind integrations, security control assessments, and exposure prioritization. Work closely with engineering to ensure research translates into accurate, scalable product features.
Set Research Quality Standards: Establish methods for validating findings, testing assumptions, and measuring accuracy. Ensure conclusions are supported by evidence and recommendations account for customer context and operational constraints.
Guide AI-Powered Research and Workflows: Shape the security knowledge, reasoning logic, and evaluation methods behind our companys AI-powered capabilities, ensuring outputs are accurate, explainable, and useful.
Partner Across our company: Collaborate with product, engineering, data, and customer-facing teams to align priorities, resolve technical challenges, and deliver meaningful customer outcomes.

Required Research Engineer, Generative Media, DeepMind
About the job
Our team's mission is to build frontier generative media experiences. We are pushing the boundaries of what is possible by developing real-time, interactive video models like Genie, as well as exciting new applications and capabilities.
We have a proven track record of researching and delivering foundational generative models for video and action-controllable virtual worlds, as well as applications such as video stylization, reference-to-video generation, and precise object insertion and removal.
Artificial intelligence will be one of humanitys most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
Design, implement, train, and evaluate novel deep learning models for real-time generative media, including video-audio synthesis, manipulation, and understanding.
Develop and optimize algorithms and systems for AI experiences on Omni platforms, focusing on live dialog, live video editing, and crosscut.
Collaborate with research scientists and engineers to prototype, experiment, and scale generative AI techniques using software engineering best practices.
Contribute to the design of datasets, evaluation methodologies, and infrastructure required for training and testing generative models.
Analyze results to iterate on architectures, contribute to research publications, and help deploy successful research into GDM and our products.