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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're looking for an Experienced Performance Researcher to join our founding team. Youll be responsible for building and optimizing scalable cloud infrastructure solutions tailored for AI workloads. This role offers a unique opportunity to directly shape our infrastructure strategy, improve system reliability and performance, and contribute to establishing us as a leader in adaptive AI compute management.
Join us to tackle the magic that make AI tick under the hood and build the backbone powering the AI revolution.
What Youll Do
- Design and build high-performance distributed inference pipelines for LLMs, focused on large-batch, non-real-time scenarios.
- Optimize GPU memory usage, kernel execution, and communication across nodes (NCCL, MPI, etc.).
- Own CUDA kernels, compiler-level tricks, and multi-GPU scheduling logic.
- Lead profiling and performance tuning for throughput, and cost- down to the kernel level.
- Collaborate with infra, product, and research teams to define SLAs, resource allocation logic, and runtime behaviors.
- Help build the core infrastructure that will run LLM workloads across hybrid GPU environments (cloud/on-prem/self-hosted).

We're looking for a talented AI Security Researcher to join our team and play a critical role in our company's foundational, risk-driven approach to cloud security. This role requires deep technical research into complex cloud- and AI-native environments to identify the most significant, unaddressed risks.
Responsibilities
Conduct deep technical research to discover and report novel risks and attack vectors specific to modern cloud- and AI-native architectures and systems.
Discover and articulate the highest unaddressed risk areas, working with Product and Engineering teams to translate research into product capabilities.
Define necessary foundational product capabilities by delivering both compelling proofs of risk (demonstrating impact) and technical POCs (showing how to solve it).
Work closely with Product and Engineering teams to ensure comprehensive risk coverage and support the investigation of new and complex product scope.

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.

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.

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

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.

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.

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 looking for an exceptional researcher at the intersection of artificial intelligence and cybersecurity. This role is intended for someone who combines deep security expertise with a practical understanding of modern AI systems and the curiosity to explore how they can be attacked, abused, and defended.
Key Responsibilities
Research vulnerabilities, attack techniques, and emerging security risks in AI models, agents, applications, and supporting infrastructure.
Develop innovative attacks, proofs of concept, evaluation methods, and defensive solutions.
Analyze how model behavior changes across problem domains, task structures, prompts, tools, resources, harnesses, and model architectures.
Translate research findings into clear security requirements, technical concepts, publications, and practical protections.
Present original research at leading international cybersecurity conferences.
Maintain a strong understanding of developments across the AI and cybersecurity landscapes.
Collaborate with security researchers, AI engineers, product teams, and other stakeholders to turn research into measurable impact.