לוח משרות דרושים הייטק AI

The Model Evaluation team is the central nervous system of the LTX Foundation Model group. We don't just measure performance; we define what "good" looks like across a vast array of use cases. While we power the next generation of creative tools, LTX is also a foundational engine for simulation pipelines, game engines, synthetic data generation, architectural rendering, and digital avatars. We act as the critical bridge between raw research and industrial-grade reliability, building the benchmarks that ensure our models are world-class for both artists and engineers.

The Role
As a Research Scientist in Model Evaluation, you are the ultimate authority on model quality and utility. You will design the automated judges, reward models, evaluation datasets, and benchmarking ecosystems that determine the future of LTX. Your mission is to provide the "ground truth" for our pre-training and post-training teams. You will blend the rigor of a researcher with the intuition of a product-thinker, developing metrics that capture both the aesthetic soul of a video and the functional precision required for high-stakes professional use.

Key Responsibilities
Steer Training & Research: Systematically evaluate model checkpoints to provide actionable insights that guide training experiments and architectural decisions.
Design Benchmark Ecosystems: Develop and run rigorous benchmarks for release candidates against competitive models, ensuring LTX-2 remains world-class.
Build Next-Gen Metrics: Develop robust automatic metrics and Reward Models (e.g., for RL, ITS, auto-research agents) that quantify complex attributes like temporal coherence, physical correctness, spatial accuracy, and foley synchronization.
Diagnose & Analyze: Perform deep root-cause analysis on model failures, providing the diagnostic clarity needed for researchers to implement targeted fixes.
Scale Evaluation: Collaborate with platform engineers to deploy evaluation frameworks across large-scale GPU clusters.

This role is designed for individuals who are not only technically proficient but also deeply passionate about pushing the boundaries of AI and machine learning through innovative engineering and collaborative research.

Key Responsibilities
Profile and optimize the training process to ensure efficiency and effectiveness, including optimizing multimodal data pipelines and data storage methods.
Develop high-performance TPU/GPU/CPU kernels and integrate advanced techniques into our training framework to maximize hardware efficiency.
Utilize knowledge of hardware features to make aggressive optimizations and advise on hardware/software co-designs.
Collaboratively develop model architectures with researchers that facilitate efficient training and inference.
Design, maintain, and evolve a high-quality, shared codebase that emphasizes correctness, readability, extensibility, testing, and long-term maintainability, while balancing performance requirements.

This role focuses on pioneering model architecture and pre-training algorithms, shaping the next generation of our foundational generative AI models.

What you will be doing
Pre-train and fine-tune video, audio, and image generative models to pursue state-of-the-art results.
Publish papers and open source models to benefit the research community and advance the field.
Design and implement machine learning models for text-to-audio and text-to-video generation.
Collaborate with data engineers to curate and preprocess text and video data.
Optimize models for high performance, ensuring efficient training and inference.
Build new controls and capabilities into generative text-to-audio and text-to-video models.
Stay updated with the latest developments in Generative AI, particularly in the fields of image, video, and audio.
Work closely with product teams to integrate AI models into applications and services.
Conduct experiments and prototype new concepts to advance the capabilities of our AI tools.

As a Research Scientist in Model Evaluation, you are the ultimate authority on model quality and utility. You will design the automated judges, reward models, evaluation datasets, and benchmarking ecosystems that determine the future of LTX. Your mission is to provide the "ground truth" for our pre-training and post-training teams. You will blend the rigor of a researcher with the intuition of a product-thinker, developing metrics that capture both the aesthetic soul of a video and the functional precision required for high-stakes professional use.

Key Responsibilities
Steer Training & Research: Systematically evaluate model checkpoints to provide actionable insights that guide training experiments and architectural decisions.
Design Benchmark Ecosystems: Develop and run rigorous benchmarks for release candidates against competitive models, ensuring LTX-2 remains world-class.
Build Next-Gen Metrics: Develop robust automatic metrics and Reward Models (e.g., for RL, ITS, auto-research agents) that quantify complex attributes like temporal coherence, physical correctness, spatial accuracy, and foley synchronization.
Diagnose & Analyze: Perform deep root-cause analysis on model failures, providing the diagnostic clarity needed for researchers to implement targeted fixes.
Scale Evaluation: Collaborate with platform engineers to deploy evaluation frameworks across large-scale GPU clusters.

We are looking for an AI Builder to design, build, and maintain agentic AI-driven workflows that streamline and automate internal business processes across the company.
This role focuses on initiating and orchestrating AI agents, integrating them with existing systems, and reducing manual effort across Sales, Marketing, Order Management, Finance, HR, and more.
You will work closely with the Information Systems team and business stakeholders to turn repetitive, human-dependent processes into reliable, AI-powered flows.
This is a hands-on builder role, not a research or pure data science position.
Key Responsibilities:
Agentic AI & Automation:
Design and implement agent-based AI workflows to automate internal processes end-to-end
Build multi-step AI agents capable of:
Decision-making
Tool usage (APIs, SaaS tools, internal systems)
Escalation and exception handling
Continuously optimize AI flows to reduce human involvement while maintaining control and auditability
AI Tooling & Platforms:
Implement solutions using Agentic AI platforms, tools and frameworks, such as: OpenAI / Azure OpenAI / Copilot Studio / Gemini Enterprise, AWS bedrock (AgentCore), SFDC Agentforce
Low-code / no-code automation tools with AI capabilities (e.g., Make, Workato, UiPath, n8n)
Select and evaluate new AI tools to support internal automation initiatives
Systems Integration:
Integrate AI agents with internal systems such as: CRM (SFDC), ERP (NetSuite), ticketing systems (Jira)
Identity and access management
Monitoring, logging, and knowledge bases
Build and consume APIs to enable agent actions and data retrieval
Governance, Reliability & Security:
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

This is your opportunity to get on the rocket ship and join a company that is building a cutting-edge enterprise network and secure cloud platform, and is on a fast track to becoming the worldwide market leader - dont miss it!
As part of this exciting journey, our company recently joined forces with Aim Security - a fast-growing innovator redefining how organizations secure and build with AI.
Backed by our companys global reach and powered by Aims startup energy, were building the future of AI Security together.
The mission is to protect how the world adopts and builds with AI - from the worlds biggest enterprises to fast-moving disruptors. We tackle hard, unsolved problems in AI, cloud, and data security - the kind that shape the next decade of technology. Our products already serve Fortune 500 customers and forward-thinking organizations worldwide, and were just getting started.
We are looking for a strong AI Engineer who wants to move into AI and and thrives in an end-to-end environment. You wont be building models in isolation. Youll join a multidisciplinary team that owns the full lifecycle of our AI Engine- from research ideas, through model serving and optimization, to monitoring and production reliability.
If youre a team-oriented engineer with strong communication skills and a passion for becoming a rockstar in the AI security space, we want you.
What youll do
End-to-End Ownership: from shaping research ideas and experimenting with models, to deploying, optimizing, and maintaining them in production.
Solve Real-World Data Problems: Tackle real-world "data-problems" to improve the reliability and accuracy of our production evaluations.
Optimize Runtime & Inference: Improve latency, throughput, and cost efficiency of our model serving stack. Think in terms of real traffic, constraints, and SLAs.
Staying Scientific: Proactively stay updated on the latest developments in NLP and AI technologies, ensuring our approaches remain at the industry's forefront.

Required staff product owner - ai solutions
company description
about us:
A palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. Our ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere.
job description
we are looking for a staff product owner to define, design, and lead innovative ai/ml products and services that shape our future in ai solutions. you will work with data science, analytics, engineering, product, architecture, and security teams to translate strategy into an actionable roadmap and ship reliable, scalable capabilities.
youll shape the ai solutions group vision, translate complex business needs into clear technical requirements, and guide r&d through execution, while staying laser-focused on quality, scalability, and measurable outcomes.
define & prioritize the backlog: gather requirements, write clear epics/user stories with acceptance criteria, and keep a well-ordered backlog aligned to objectives.
drive delivery: lead/participate in agile ceremonies including daily stand-ups, planning, reviews & retros.
bridge business & technology: translate business problems into technical requirements; ensure teams understand goals and trade-offs.
lead cross-functional execution: partner across company teams to remove blockers and land initiatives end-to-end.
advance ai/ml capabilities: drive innovation across supervised/unsupervised learning, anomaly detection, and genai/llms.
champion production ml: mlops best practices, data governance, explainability, monitoring, rbac approvals/audit, and cost/latency budgets.

a palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere. learn more. job description
we are looking for a senior ai software engineer to join our generative ai foundation team. we build ai agents and shared infrastructure that power genai capabilities across the company, enabling product lines to adopt agentic workflows safely, reliably, and at scale.
in this role, youll be involved in the full software lifecycle - from fast-moving prototypes and pocs to production-grade, observable systems. youll collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence.
youll work hands-on with leading llms and the modern agentic ecosystem, leveraging a wide range of aws services. youll use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve our solutions through solid design, flexible implementation, strong telemetry and evaluation, and production feedback loops

We are looking for a Knowledge & AI Enablement Manager with proven experience in Knowledge Management and AI driven systems to design, build, and own the complete Knowledge Lifecycle for Technical Support.
This role defines how operational knowledge is created, governed, maintained, and embedded into daily Support workflows, while ensuring it is AI ready and serves as a trusted, high quality input for AI models across the organization.
Key Responsibilities:
Knowledge Lifecycle Ownership:
Own and build the end-to-end Knowledge Lifecycle for Support, from case-driven knowledge creation through continuous improvement and reuse
Define how knowledge is captured from cases, incidents, and escalations and transformed into structured, reusable, high-impact assets
Establish governance models for knowledge quality, validation, ownership, versioning, and ongoing maintenance
Design and operationalize workflows that embed knowledge creation, review, and updates into daily Support activitie
Define and implement a RACI model for knowledge creation, review, approval, and maintenance
Knowledge and AI Readiness:
Own KM platform configuration, Search and analytics tooling, taxonomy, publishing workflows, and integration with case management and AI retrieval pipelines
Define and enforce standards that ensure Support knowledge is structured, tagged, and maintained to be fully consumable by AI systems such as LLMs, RAG pipelines, semantic search, automation, and recommendation engines
Partner closely with Data, AI, and Engineering teams to align knowledge models, structure, and lifecycle with AI consumption requirements and future AI roadmaps
Act as the primary owner of the Support knowledge layer that feeds AI, ensuring consistency, reliability, and scalability
Measurement, Feedback, and Adoption
Define, track, and continuously improve KPIs including knowledge coverage, freshness, reuse, case deflection, and measurable AI performance impact
Establish feedback loops that surface insights from AI usage and knowledge gaps back to Support Engineers, driving better case handling and higher quality knowledge creation
Lead change management initiatives to drive adoption, accountability, and consistent knowledge behaviors across global Support teams.

Were looking for a Data Analyst to join the Data for AI team. This is a hands-on, customer-facing role focused on working with leading AI companies to turn real-world data into inputs that support model development and evaluation.
Youll collaborate closely with external AI teams and internal engineering and product partners to deliver data-driven solutions for specific AI use cases. The work is fast-paced, technical, and often open-ended, requiring comfort with large datasets, ambiguous requirements, and end-to-end ownership.
What does the day-to-day looks like:
Own end-to-end delivery of data solutions for AI use cases, from understanding model and product requirements to analysis, implementation, quality, and automation
Work hands-on with large, raw datasets to create high-quality data inputs that support model training, evaluation, and iteration
Apply strong quantitative analysis and data exploration skills to assess coverage, quality, and behavior of data used in AI systems
Build scripts, analyses, and reusable components in Python and SQL to support scalable and repeatable workflows
Collaborate closely with Engineering to ensure solutions are reliable, scalable, and production-ready
Partner directly with external AI teams and internal stakeholders to translate open-ended questions into concrete data outputs.

As an AI Engineer at our company, you will be a key player in building our new AI platform, AI Studio. This platform aims to provide users with instant answers to complex market research questions, generate world-class reports, and create live, interactive, and powerful dashboards. Our goal is to reduce the complexity and time-to-insight for our users, helping them streamline their market tasks and achieve automation that drives real value.
So, what will you be doing all day?
Design and develop LLM-based intelligent agents that can handle complex market research queries.
Utilize LangGraph and other frameworks to create state of the art AI agents that integrate various tools and data sources.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Collaborate with product, data, and UX teams to ensure that AI solutions are aligned with user needs and business goals.
Continuously evaluate and improve the performance of AI models to ensure high-quality and data-driven results.

Were looking for a Backend AI Engineer to own and build agentic AI architecture. This role sits at the intersection of backend engineering and production-grade AI systems. Youll design, build, and scale the backend that powers our AI creators, enabling intelligent, reliable, and observable agentic workflows at scale.
Youll work on orchestrating multi-step AI workflows that involve LLMs, tools, and decision logic, and ensure they operate reliably under high load and real-world usage. A key part of the role is designing systems that can handle non-deterministic AI behavior, recover gracefully from failures, and continue to perform as usage and complexity grow. Youll also be responsible for making architectural decisions that support scalability, low latency, and long-term maintainability of our AI platform.

We are looking for an experienced and dynamic Team Lead to manage a talented group of frontend & backend engineers, qa testers and devops. In this role, you will oversee the design , development and delivery of versions of our software to our biggest customer, ensuring that it meets the highest standards of quality and efficiency.
Additionally, you will collaborate closely with stakeholders in the customer team and within the organization, requiring strong communication and leadership skills.
Key Responsibilities:
Lead, mentor, and manage a hybrid team (Onshore & Offshore) of 10 engineers (frontend, backend, quality, devops), fostering a collaborative and high-performance culture.
Oversee our AI-first transformation in your team- moving all coders to do 100% vibe coding
Collaborate with product owners, QA, DevOps, and other team members to deliver high-quality software solutions within an Agile framework.
Ensure the teams not only develop features but also write comprehensive automation tests to validate and cover their work, ensuring high quality and stability.
Ensure designs and implementations align with technical specifications, industry standards, and best practices.
Promote continuous improvement by exploring and adopting new technologies and methodologies.
Provide support for customer and delivery teams in successfully implementing projects based on the platform.
Contribute to all phases of the development lifecycle, from design through deployment to maintenance.
Write well-structured, testable, and efficient code when needed.