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This is a research‑first role focused on deeply understanding LLM internals to improve the security of AI agents. Youll design careful experiments on activations and interpretable features- e.g., probing, attribution & ablation/patching, representation‑geometry analyses-to uncover mechanisms behind jailbreak, indirect prompt injection, and other attacks. Then translate those insights into signals that can be used for detection and analysis of a model response.
The field of LLM interpretability at scale is exploding, with several major publications in the last months, and major opportunities for innovation.
What Youll Do:
Investigate model internals, including activation/features analysis, unsupervised clustering, discovery of directions in latent space, etc. It may also require training specific model parts to improve interpretability metrics.
Design security‑grounded evaluations: curate datasets for different attack types, evaluate performance of different white box (model internals) methods compared to black box (input/output only) baselines.
Publish and share: produce Labs posts and open artifacts; when the work is strong, aim for tier‑1 ML venues (NeurIPS, ICML, etc.) and security forums. A publication of code and/or trained models in cases of community relevant novelty.
Build tools: Several open source libraries exist (like Anthropics attribution graphs infra), but the research in the field is very dynamic, which will require you to build and adapt tools to your own research directions. This also includes agents to automate research work and distill knowledge from designed experiments.

We are seeking a Senior AI Researcher Reporting to CEO .
This role is pivotal, aimed at addressing some of the AI industry's most complex challenges. Senior AI Researcher will act as a versatile 'joker card' within the R&D, stepping in to expedite projects, solve bottlenecks, and provide specialized expertise as needed. This role is designed to minimize latency and accelerate outcomes across various technical domains within the company. The ideal candidate will have strong technical expertise, excellent coding skills, and the ability to solve problems effectively.
The role doesn't include managerial responsibilities but does involve close collaboration with internal teams and the capability to inspire and guide staff. As a professional authority within our teams, the Technology Director will improve quality and speed up problem resolution. Adeptness in analyzing complex issues quickly, switching contexts when needed, and fostering a culture of growth and technical excellence is also desired.

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.

This team builds the core scanning logic that allows our company to operate at true enterprise scale. Its mission is to expand data coverage and increase scanning efficiency by designing intelligent processing strategies, heuristics, and models tailored to different data types and environments. By making scanning faster, more scalable, and more cost-effective, the team enables our company to analyze vastly more data across customer estates-turning large-scale classification from a theoretical capability into a practical, affordable reality for organizations of any size.
What Youll Do
Lead applied research to improve large-scale data scanning, from hypothesis formulation to validation and impact measurement.
Investigate system and data behavior at scale to surface constraints and opportunities for smarter scanning.
Design heuristics and processing logic that scale the product while keeping classification quality as a north star.
Translate research findings into scalable, production-ready solutions under real system constraints.
Collaborate closely with data science, engineering, and product teams to influence product decisions through data-driven insights.

We are building a new software engineering team with strong applied AI orientation to amplify success. The team will be focusing on creating company-wide applications to address our colleagues every day problems. You will have a chance to work with a broad range of teams , helping them to be more productive with custom solutions.
Collaborate with cross-functional distributed teams.
Gather, analyze and spec out requirements, and manage product deliverables.
Design and build scalable AI-driven products addressing real-world problems.
Stay current with the latest technical advancements, particularly in the field of AI and LLMs.

We are looking for an AI Engineer to play a central role in building, evaluating, and advancing Immunais AI models. You will own and evolve Immunais 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.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Own & Evolve Benchmarking - Design, build, and maintain Immunais 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.

As the Product Manager for the AI models of core product offering, you will be responsible for defining and driving its product strategy, requirements, roadmap and delivery.

The product focuses on addressing real-world challenges in drug development by leveraging AI foundation models and multi-omic data to map and predict human immune response.

You will be working closely with our team of Data Scientists, Computational Biologists, Deep Learning Researchers and Engineers.

Location: Ramat Gan, Israel (Hybrid model)

What will you do?

Set the long-term vision and strategy for AI models, ensuring alignment with company goals.
Define product requirements and build a clear, prioritized roadmap for model development and delivery.
Lead benchmarking efforts to evaluate model performance against internal baselines and external best-in-class models.
Collaborate with AI research, data science, engineering, and biologists to translate scientific advances into scalable product capabilities.
Oversee the end-to-end lifecycle of AI models, including data strategy, training priorities, evaluation criteria, releases, and post-deployment monitoring.
Identify, validate, and prioritize high-impact use cases where improved model capabilities create meaningful business or scientific value.
Communicate strategy, progress, and key decisions to leadership and cross-functional stakeholders to drive alignment.

We are looking for a driven and experienced leader to manage a growing interdisciplinary team of LLM Agentic AI Researchers, Computational Biologists, and Immunologists. This teams mission is to build a cutting-edge agentic reasoning system powered by Large Language Models (LLMs), capable of generating structured, biologically grounded sequential explanations based on predictions from proprietary foundation model-trained on hundreds of millions of immune cells. The product the team builds is a pillar of AI strategy, with the potential to redefine the way a drugs mode of action is understood.

Location: Ramat Gan, Israel (hybrid model)

What You'll Do:

Set the Vision - Collaborate with product leadership to transform bold ideas into AI capabilities that impact real-world medical decisions.
Build and Lead the Team - Coach, build and inspire a high-caliber team across LLMs, data science, and Immunology. Cultivate a culture of excellence, curiosity, and execution.
Drive Innovation - Lead from the front-design architectures, write prototypes, and guide technical direction. Lead the team in building agents that reason about biological systems at scale.
Ship Transformative Products - Deliver AI products & solutions that move the needle and its partners - from static biological associations to dynamic, explanatory models of causality.
Showcase Leadership - Represent the team in top-tier scientific conferences and publications, communicating groundbreaking research to the world.

Were looking for an independent, curious AI researcher to join and help bring generative AI into high-precision financial workflows. Youll turn research ideas into robust, production-grade features that meet finances strict correctness and auditability requirements.
we are a SaaS B2B solution solving one of the biggest challenges in finance: transforming scattered Excel-based processes into streamlined, cloud-based systems. We help finance professionals gain control, clarity, and insight over their data - from reports to forecasts to deep analytics.
What You'll Do:
Own end-to-end projects: define the problem, prototype, evaluate, and deliver PoC/MVPs.
Research and build GenAI solutions, flows, and agents that reduce nondeterminism and produce numerically reliable outputs for financial use cases.
Design practical verification, monitoring, and fallback strategies so GenAI can be trusted in critical workflows.
Collaborate with engineering and product teams to ship and maintain production solutions.

Required AI Insights and Research Specialist
Realize your potential by joining the leading performance-driven advertising company!
Our Strategy and Intelligence team is building an execution-first, impact-driven capability to turn data and generative AI into a core advantage for our marketing organization and beyond. We operate with startup intensity, enterprise reach, and a relentless drive for actionable insights.
As an AI Insights and Research Specialist on the Strategy and Intelligence team in our Tel Aviv Office, youll play a vital role in owning the in-depth understanding of our customer portfolio and market landscape. This role is perfect for a data-savvy analyst who thrives on uncovering best practices and is eager to build and leverage AI tools and agents to scale their impact.
Youll be a key player in a high-impact Strategy and Intelligence team with direct visibility and ownership. Were not just analyzing data the traditional way; were operationalizing AI to revolutionize how we understand our customers and market. If you like lean teams, cross-functional execution, and using cutting-edge tech to solve real business problems, this is your home.
How youll make an impact:
Lead in-depth analysis of customer activity data to uncover trends, best practices, and actionable insights for the marketing organization and broader company.
Monitor and report on key performance indicators (KPIs) regarding our customer portfolio, providing data-driven recommendations to strategy leadership.
Conduct external industry research to benchmark us against market standards and identify emerging opportunities, including leveraging industry databases.
Own end-to-end implementation of GenAI and automation projects in order to fulfill the above tasks and more - from scoping and prompt design to testing, documentation, and rollout.
Translate business needs into structured workflows, coordinating between non-technical and technical teams.
Translate complex data into clear, strategic narratives that drive decision-making across marketing and business teams.
Execute all of the above using AI tools extensively (AI first) to increase pace and quality of outputs.

As a GenAI Security Researcher, you’ll be deep diving into AI security challenges by running red teaming operations to find weaknesses in generative AI systems and their setup. Pioneering novel bypass techniques to test the latest AI security defenses. Identifying system flaws, driving remediation efforts, and fortifying overall AI security to help building robust, secure, and future-ready models. Partnering with teams to automate security testing and define enterprise best practices. Staying ahead of the curve in AI security, ethical hack.

About Alice:
Alice is 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, Alice 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.

This is not a researcher or data science role. Its a solution-driven, execution-oriented position for someone who knows what LLMs can do, and how to make them deliver value today.



Key Responsibilities:

Design AI-powered solutions using off-the-shelf tools and APIs (prompting, chaining, agents, etc.)
Collaborate with product and R&D teams to deliver working features and PoCs
Own the how of AI: from idea to prototype to functional integration
Track AI industry trends and apply relevant ideas and tools
Act as a cross-functional bridge between product, tech, and innovation

You will:
Design and execute research projects using advanced methodologies and tools to generate actionable insights that improve decision-making.
Analyze data and apply critical thinking to identify innovation opportunities and optimize research processes.
Prepare scientific reports and presentations to effectively communicate findings and recommendations to stakeholders.
Collaborate across teams and consult with experts, demonstrating adaptability, receptiveness to feedback.

We are looking for a talented AI Researcher to join our Wi-Fi MAC team and help shape the next generation of intelligent wireless systems. This role sits at the intersection of AI/ML and advanced Wi-Fi technologies, focusing on applying machine learning to complex Wi-Fi scenarios and, conversely, adapting Wi-Fi systems to better support AI workloads - AI for Wi-Fi and Wi-Fi for AI.
You will work closely with Wi-Fi protocol experts to explore, design, and prototype AI-driven solutions for MAC-layer optimization, performance enhancement, and intelligent decision-making in real-world wireless environments.
Key Responsibilities
Research and develop AI/ML techniques for Wi-Fi MAC-layer challenges (e.g., scheduling, rate control, congestion management, fairness, latency, and reliability).
Embed AI models into complex Wi-Fi system setups and scenarios, including dense networks and multi-user environments.
Analyze large-scale Wi-Fi datasets, simulations, and traces to train and evaluate ML models.
Collaborate with Wi-Fi experts to translate protocol behavior into ML-friendly features and learning objectives.
Explore how Wi-Fi systems can be optimized to support AI workloads, including data collection, inference efficiency, and real-time constraints.
Prototype, test, and validate ideas using simulation tools, testbeds, or experimental platforms.
Contribute to technical documentation, design discussions, and long-term architectural decisions.

As the AI Research Team Lead, you will lead a specialized team of researchers focused on high-performance AI systems, including GPU optimization, networking architectures, and collective communication strategies. You will define research directions, mentor the team, and collaborate closely with major industry players to align research with real-world applications and standards.
Key Responsibilities
● Lead and manage a team of AI researchers focused on GPU acceleration, networking, and collective communication.
● Define and execute research strategies aligned with company and industry goals.
● Conduct advanced research in AI infrastructure, distributed training, model optimization, and high-performance computing.
● Translate research findings into practical solutions for production-scale AI systems.
● Collaborate with leading industry companies to align research with emerging standards and real-world challenges.
● Identify bottlenecks, analysis and optimize in distributed GPU eco-system
● Participate in code reviews and technical design discussions.