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We are looking for a Senior AI Researcher to join our foundation models team and help advance large-scale models for single-cell RNA (scRNA) data.
In this role, you will focus on training and improving transformer-based and deep learning models, developing algorithmic solutions to challenging modeling problems, and adapting modern foundation model techniques to biological data. This is a hands-on research position for someone who enjoys building and training deep models, understanding their behavior, and pushing them to perform better.
You do not need prior biology experience - but you should be excited to apply your deep learning expertise to a new scientific domain.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Develop, train, and refine transformer-based and related architectures for large-scale scRNA data.
Tackle challenging modeling problems with thoughtful, principled approaches.
Apply ideas from NLP and vision (pretraining, self-supervision, transfer learning) to biological data.
Plan careful experiments, perform ablations, and deeply analyze results to guide model improvements.
Engage directly with large, noisy biological datasets and build intuition for model behavior in this setting.
Partner with engineers, data scientists, and biology experts to turn research ideas into working systems.

As an AI Researcher, youll be part of the team building the AI systems that power our products. Youll work across research and engineering - from training and post-training state-of-the-art LLMs to applying them to challenging real-world problems such as agentic behavior, coding, and security-related decision-making.

This is a hands-on research role with a strong focus on taking ideas from experimentation to production. Youll have significant ownership and the opportunity to shape both the direction of our AI research and the systems we build around it.

WHAT YOU WILL DO
Train, adapt, and scale state-of-the-art LLMs using techniques such as post-training SFT, knowledge distillation, LoRA, and reinforcement learning.
Develop and evaluate new algorithms and approaches, bridging cutting-edge academic research with production-grade AI systems.
Optimize models for production, balancing quality, latency, throughput, and cost at scale.
Own the AI lifecycle-from algorithmic prototyping and synthetic data generation to evaluation, deployment, and iteration of production AI features.
Work closely with engineering and product teams to translate research advances into impactful AI capabilities.
Lead research initiatives that advance the capabilities of our AI systems.

Join our company, a stealth-mode cybersecurity startup building the next generation of Vulnerability Management and Exposure Management.
Were looking for a Senior AI Researcher (Cyber Security) to join our founding team and build AI-powered product capabilities that enable unprecedented effectiveness in vulnerability and asset management.
In this role, youll work hands-on with large-scale security data (assets, vulnerabilities, exposure context) and design production-grade AI systems that turn messy, complex information into clear, actionable insights.
Own the end-to-end AI lifecycle: from feature ideation and initial research, through data exploration and model development, to delivering reliable, production-grade capabilities. Validate solutions in controlled testing and continuously monitor, evaluate, and improve performance in production.
If you love combining real security problems with applied data science and AI driven problem solving, and want to have real impact in a rapidly evolving product - wed love to meet you.

Were hiring a Senior AI Analyst to join our Research team and help shape our AI-driven cybersecurity platform. In this role, youll dig deep into how our AI agents perform, uncover whats working and where the opportunities are, and turn that analysis into insights that shape the roadmap, strengthen the product, and drive customer value and growth.
What Youll Do
Run deep-dive analyses on how our AI agents and product features perform - uncovering patterns, edge cases, and the biggest opportunities to improve.
Define and track the metrics that measure the performance and impact of our AI-driven capabilities.
Turn those insights into prioritized product direction, partnering with product and engineering to influence what we build next.
Work directly with customers and field teams to fold their needs and feedback into that direction, strengthening the outcomes that drive customer value and growth.
Build automations, tools, and pipelines that scale analysis and internal processes.

Required Senior Applied AI Researcher- Sovereign AI Research
About The Position
Nations are waking up to a hard truth: critical intelligence infrastructure built on hyperscaler black boxes isn't a solution it's a dependency. The Sovereign AI Research Group exists to answer that differently.
We're not fine-tuning what already exists. We're rethinking the models architecture from the ground up modular, composable, and built with compute governance as a first-class design constraint, not an afterthought.
We operate under real-world constraints. The interesting problems live at the intersections of disciplines. That's where we operate.
This is a hands-on research role embedded within a team of senior researchers. Day to day includes training models, running benchmarks, synthesize data. The researchers you'll work alongside will challenge you technically and invest in your growth.
Responsibilities:
Open Research Tracks
Familiarity with at least one is expected:
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Train and evaluate models across research tracks, iterating fast while documenting rigorously.
Build and maintain benchmarking pipelines and evaluation suites.
Curate, structure, and preprocess datasets; contribute to synthetic data generation workflows.
Run ablations and controlled experiments to support research hypotheses.
Reproduce and stress-test results from recent literature relevant to the group's work.
Collaborate across tracks and with engineering teams through to production handoff.

We are seeking a Senior Applied Researcher/ Data Scientist to join our core product organization, where you will build and deploy next-generation AI models powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). The role centers on building and scaling intelligent systems powered by LLMs, advanced ML techniques, and agent-based architectures.
You will join a team within our Cyber R&D organization, leading the companys core product portfolio-while driving AI innovation and setting best practices across the domain. The group focuses on developing next-generation technologies, including training and optimizing LLMs and building advanced multi-agent workflows, while mentoring data scientists across R&D.
As a key technical leader, you will guide the evolution of our AI capabilities-converting cutting-edge ideas into impactful, production-ready systems and shaping our long-term direction.
We are looking for visionary applied researchers eager to take on ambitious challenges and push the boundaries of AI in cybersecurity.
Responsibilities
Design and build advanced AI models and systems that power our core products and address real-world cybersecurity challenges.
Own initiatives end-to-end from identifying customer-driven problems and shaping solutions to experimentation, prototyping, and production deployment.
Drive forward new ideas and research directions, turning emerging concepts into practical, scalable solutions.
Influence the organizations roadmap and contribute to long-term technical strategy across our AI and product landscape.

We are looking for a talented AI Applied Researcher to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.
What Youll Do:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Collaborate with engineering teams to design, build, and maintain production pipelines.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

Required Sr. Principal AI Researcher, AI Transformation
Job Summary
Shape the future of AI-powered software engineering. As part of our AI Transformation group, youll join a multidisciplinary group building state-of-the-art, agentic AI systems that directly elevate the productivity of thousands of internal engineers.
We build internal AI infrastructure, frameworks, agents, harnesses, methodologies, and adoption programs powered by cutting-edge LLMs. Whether you are researching novel AI paradigms, architecting platform infrastructure, engineering end-to-end agentic tools, or driving developer enablement, your work will redefine how software gets built at scale.
This is an applied AI research role, where you will be inventing new technology, bringing the latest innovations into our agentic software development practices, and responsible for co-building systems that get deployed to our entire, global Cortex engineering organization.
Key Responsibilities:
Stay at the forefront of AI advancements in agentic coding and integrate state-of-the-art techniques.
Build functional Proof of Concepts (PoCs) and architectural skeletons to evaluate new AI techniques before scaling.
Critically audit and challenge internal AI solutions, benchmarks, and architectures to prevent technological obsolescence.
Design rigorous testing methodologies to assess model accuracy, latency, cost efficiency, and drift across solutions.
Research and design advanced knowledge-retrieval architectures, including standard and graph-based RAG and hybrid contextual search.
Collaborate with core AI engineering to transition validated prototypes into reusable components for our engineering workforce.
Coordinate closely with the US Foundational AI Research team via flexible evening Israel / morning US meetings.

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 research team to develop the next generation of multimodal video diffusion models and bring cutting-edge research into real-time products used at global scale.
About the Team:
Our research team is small, fast-moving, and highly impactful. We develop multimodal generative models for real-time video creation, turning cutting-edge research into scalable products.
We are looking for researchers with deep expertise in generative video to join a team at the core of technology and help shape the future of generative AI.
Why Work ?
Work on cutting-edge video-generation technology at the forefront of AI.
See your research become part of products used at global scale.
Own meaningful research and engineering challenges as part of a small, high-impact team.
Help solve complex problems in real-time video generation.
Build technology that brings the next generation of AI assistants to life.

Shape the future of AI-powered software engineering at Palo Alto Networks. As part of our AI Transformation group, youll join a multidisciplinary group building state-of-the-art, agentic AI systems that directly elevate the productivity of thousands of internal engineers.
We build internal AI infrastructure, frameworks, agents, harnesses, methodologies, and adoption programs powered by cutting-edge LLMs. Whether you are researching novel AI paradigms, architecting platform infrastructure, engineering end-to-end agentic tools, or driving developer enablement, your work will redefine how software at Palo Alto Networks gets built at scale.
This is an applied AI research role, where you will be inventing new technology, bringing the latest innovations into our agentic software development practices, and responsible for co-building systems that get deployed to our entire, global Cortex engineering organization.
Key Responsibilities
Stay at the forefront of AI advancements in agentic coding and integrate state-of-the-art techniques.
Build functional Proof of Concepts (PoCs) and architectural skeletons to evaluate new AI techniques before scaling.
Critically audit and challenge internal AI solutions, benchmarks, and architectures to prevent technological obsolescence.
Design rigorous testing methodologies to assess model accuracy, latency, cost efficiency, and drift across solutions.
Research and design advanced knowledge-retrieval architectures, including standard and graph-based RAG and hybrid contextual search.
Collaborate with core AI engineering to transition validated prototypes into reusable components for our engineering workforce.
Coordinate closely with the US Foundational AI Research team via flexible evening Israel / morning US meetings.

We are seeking a highly accomplished AI Researcher to be part of the development of next-generation Foundation Models and Generative AI systems. In this role, you will bridge the gap between cutting-edge academic research and production-grade AI infrastructure. You will build, design, and fine-tune large-scale architectures (including LLMs, Multimodal, and Tabular Foundation Models) while applying them to complex, real-world domains like agentic behavior, coding and decision making.
In your day-to-day, you will:
Conduct pioneering research in deep learning and generative AI, specializing in Foundation Models, NLP, alignment, and multimodal learning
Deal with the impact of the models on production traffic, cost quality and latency
Train and scale state-of-the-art architectures using techniques like Post-Training SFT, Knowledge Distillation, LoRA, and sparse/hybrid model architectures
Own the AI lifecycle-from algorithmic prototyping and synthetic data generation to deploying production-grade AI features in fast-paced or big-data environments
Drive research initiatives, author publications/patents, and collaborate with other research teams to integrate intelligent capabilities into core products.

Requred AI Researcher
What will your job look like:
Design, implement, and train state-of-the-art neural network architectures for robotic applications, including large multimodal models (vision, language, sensor data) and generative models.
Architect and maintain scalable deep learning frameworks for training on massive, real-world robot datasets.
Develop and implement cutting-edge techniques in areas such as imitation learning, reinforcement learning, self-supervised learning, and video-based models.
Own the full machine learning lifecycle: define data collection and labeling strategies, build high-throughput data pipelines, and establish robust evaluation and deployment protocols.
Collaborate closely with software, hardware, and controls teams to integrate and test your models on physical robots.
Leverage and contribute to internal tooling for large-scale data processing, model experimentation, and continuous integration.

We are looking for an AI Researcher to help build the intelligence behind our AI security platform.

This is a hands-on research role focused on understanding how modern large language models and AI agents behave, identifying new attack vectors and protection techniques, and translating cutting-edge research into production-ready capabilities. The intelligence developed by this team is a core differentiator of our platform and a key driver of the company's success.

You will work at the intersection of machine learning, LLMs, and cybersecurity, partnering closely with AI engineers and product teams to develop technologies that directly power our product. We're looking for someone who enjoys understanding how neural networks and foundation models work, pushes the boundaries of AI research, and is excited to see their work deployed into production and used by customers.

What you will do
Research the behavior, capabilities, and limitations of modern large language models and AI agents.
Design novel techniques for detecting, evaluating, and proactively protecting against AI threats, prompt injection, model misuse, and emerging attack vectors.
Develop new approaches for securing AI systems and improving the intelligence that powers our platform.
Design and run experiments to evaluate model behavior, validate new ideas, and measure the effectiveness of protection techniques.
Build research prototypes and turn them into production-ready capabilities.
Work closely with Product and Engineering to translate research into scalable product features.
Stay current with advances in LLMs, foundation models, post-training techniques, AI security, and AI safety.
Contribute to the long-term technical direction of our AI security platform.

Senior AI Research Engineers at Simply develop algorithmic solutions that power new innovative features and continuously improve existing ones, with a strong emphasis on training AI / ML models as a core part of the role. The work spans a wide range of domains - from training generative AI and LLM-based models to create musical content at scale for Simply Piano, through building deep learning computer vision models that enhance user drawings in Simply Draw, to developing real-time audio ML models for music transcription that elevate feedback.

You will take full end-to-end ownership of cutting-edge algorithms and AI models - leading the process from ideation and research, through development, to production-grade implementation and engineering within products. This includes not only designing and building AI models, but also ensuring robust, efficient, and scalable integration into the app - directly shaping the experience of millions of users.