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As an ML Software Engineer with a focus on low-level and CUDA-based optimizations, you will play a key role in shaping the design, performance, and scalability of machine learning inference systems. Youll work on deeply technical challenges at the intersection of GPU acceleration, systems architecture, and ML deployment.
Your expertise in CUDA, C/C++, and performance tuning will be crucial in enhancing runtime efficiency across heterogeneous computing environments. Youll collaborate with designers, researchers, and backend engineers to build production-grade ML pipelines that are optimized for latency, throughput, and memory use, contributing directly to the infrastructure powering next-generation AI products.This role is ideal for an engineer with strong systems-level thinking, deep familiarity with GPU internals, and a passion for pushing the boundaries of performance and efficiency in machine learning infrastructure.

Responsibilities
Design and implement highly optimized GPU-accelerated ML inference systems using CUDA and low-level parallelism techniques
Optimize memory, compute, and data flow to meet real-time or high-throughput constraints
Improve the performance, reliability, and observability of our inference backend across diverse compute targets (CPU/GPU)
Collaborate with cross-functional teams (including researchers, developers, and designers) to deliver efficient and scalable inference solutions
Contribute to ComfyUI and internal infrastructure to improve usability and performance of model execution flows
Investigate performance bottlenecks at all levels of the stack-from Python to kernel-level execution
Navigate and enhance a large, complex, production-grade codebase
Drive innovation in low-level system design to support future ML workloads

Youll play a key role in shaping the tone, style, and visual language of LTX Studios product assets, making sure every asset feels polished, clear, and aligned with the product experience. This is a hands-on role for a designer with strong visual taste, sharp motion skills, and the ability to turn product needs into compelling creative.

Youll collaborate closely with Product Design, Brand, and Product teams to help define how LTX Studio looks, feels, and communicates to users and partners.

What you will be doing
Design high-quality visual and motion assets for LTX Studio
Create in-product assets such as banners, pop-ups, and visual components
Produce motion design assets using Adobe tools, especially After Effects
Support product demos and partner presentations with compelling visuals
Collaborate cross-functionally with Product Design, Brand, and Product teams
Maintain a strong visual identity and high design quality across all assets
Iterate quickly as the product evolves and new needs emerge

We are seeking a researcher to join the LTX Model Applications team, focusing on advancing and extending the capabilities of our LTX-Video models. You will design and explore new use cases, train novel ways to control the generation process, and push the boundaries of generative video technology. Your work will directly influence millions of users through our apps and contribute to the broader research and open-source communities, shaping the next generation of creative tools.

What you will be doing
Advance and extend the capabilities of our LTX-Video models through new controls, features, and use cases.
Design and implement machine learning models for video, image, and audio generation, as well as multimodal applications.
Conduct experiments, prototype concepts, and validate ideas to expand generative video technology.
Collaborate with engineers, designers, and product managers to translate research into impactful product features.
Regularly open-source code, models, and research insights, contributing to the academic and open-source communities.
Stay at the forefront of generative AI research in video, image, and audio, and bring relevant advances into our products.
Write high-quality, efficient code and maintain best practices in research workflows.
Mentor other researchers and lead collaborative projects.

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.

About the position This full-time position is based in Tel Aviv (Ahad Ha'am st) and will report directly to the Site Manager. As a receptionist, you will be the first point of contact for members and guests, ensuring a smooth and welcoming experience. A key part of your role will be managing the reception area, handling administrative tasks, and supporting the community and operations teams. This position is ideal for someone with strong organizational skills who thrives in a front-facing, service-oriented role and enjoys performing clerical work in a dynamic environment. Responsibilities
* Manage the front desk during operational hours, ensuring a welcoming and professional atmosphere
* Serve as the first point of contact (POC) for all members and guests at Mindspace
* Handle administrative tasks such as managing mail, shipping, supplies, and office equipment
* Organize office operations and procedures to maintain efficiency
* Support the Community Managers with various community-related tasks
* Address and resolve member inquiries and issues promptly
* Assist with facility operations, maintenance coordination, and vendor management #LI-Onsite

The Sales Engineer acts as the bridge between engineering and business. Responsible for translating customer needs into technical and commercial solutions, supporting Presale and project execution, and developing technical-marketing assets.

As a Large Scale Training Engineer, you will play a key role in enhancing the training throughput of our internal framework and enabling researchers to pioneer new model concepts. This role demands excellent engineering skills for designing, implementing, and optimizing cutting-edge AI models, alongside writing robust machine learning code and understanding supercomputer performance deeply. Your expertise in performance optimization, understanding distributed systems, and bug elimination will be crucial, as our framework supports extensive computations across numerous virtual machines.

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 Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.

What you will be doing
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.

Your Career The Cortex Cloud Identity Security product is responsible for helping customers understand who has access to what data and resources in their multi-cloud and SaaS environments, and critically, what their true effective permissions are. Identity is the new control plane and the most exploited attack vector in the cloud and in SaaS; this product eliminates the lateral movement and privilege escalation risks caused by excessive and unused permissions. We are looking for a Principal Product Manager who can design, build and ship industry defining products to help cloud security and identity security teams protect their organization's identities across their cloud and SaaS environments. Your Impact Build and launch enterprise class products throughout the entire product lifecycle - collect customers feedback and hear their need, prioritize features and trade offs, write the product requirements and work closely with engineering group to deliver the roadmap Lead core pillars within Cortex Cloud Identity Security and grow them to new horizons by bringing innovative and disruptive approaches, and ensure that they can be effectively launched Working effectively with all areas of the organization in a global company, from engineering to sales Understand cloud and identity security practitioners, often being able to directly relate to and understand use cases Work closely with our customer success, marketing and sales teams on supporting existing customers, identifying common user problems and taking the solutions you define to market.

As a Site Reliability Engineer on the SASE Platform team, you will play a critical role in building and operating highly available, secure, and globally distributed services. Your mission is to ensure our cloud-native security and networking platform is reliable, scalable, and performant from day one, protecting the users, applications, and data for the world's largest enterprises as they adopt cloud, remote work, and AI
Your Impact:
Proactively collaborate with development teams to embed reliability, scalability, and operability into services from the earliest design stages.
Design, review, and evolve cloud-native architectures to improve availability, performance, cost efficiency, and fault tolerance.
Build and operate automation for provisioning, deploying, and managing global infrastructure using Infrastructure as Code (IaC).
Improve CI/CD pipelines and release processes to enable safe, fast, and repeatable deployments.
Drive observability best practices, including metrics, logs, traces, and SLIs/SLOs to enable data-driven incident analysis.
Participate in on-call rotations, reducing mean time to resolution (MTTR) through automation and proactive reliability improvements.
Challenge existing processes by championing reliability, security, and operational maturity across the organization.

As a Principal Product Manager for Cortex Cloud Application Security (CAS), you will be at the forefront of securing the development ecosystem from code to deployment. You will help design, build, and ship industry-defining products that facilitate "shift left" security operations. Your work will directly empower application security teams and developers to build more secure cloud applications by identifying and remediating risks across IaC, source code, open-source libraries, and CI/CD pipelines.
Key Responsibilities
Manage the entire product lifecycle for key areas of Cortex Cloud CAS, from customer feedback collection and feature prioritization to writing product requirements and working with engineering to deliver the roadmap.
Lead core pillars within the CAS product, driving growth by bringing innovative and disruptive approaches to solve complex application security challenges.
Collaborate effectively with cross-functional teams across a global organization, including engineering, sales, marketing, and customer success, to ensure product alignment and successful launches.
Develop a deep understanding of DevOps and Application Security practitioner workflows and use cases to guide product strategy and ensure solutions meet customer needs.
Partner with go-to-market teams to support existing customers, identify common user problems, and effectively launch new solutions and features.
Take ownership of new technology products and their full lifecycle, ensuring they meet enterprise-class standards and deliver value to customers.

We are seeking a Principal Product Manager for our Cortex Cloud Identity Security team. In this role, you will design, build, and ship industry-defining products that help customers manage identity and access in their multi-cloud and SaaS environments. You will be instrumental in eliminating risks from excessive permissions and protecting organizations from identity-based attacks, the most exploited vector in the cloud.
Key Responsibilities
Manage the entire product lifecycle from customer feedback collection and feature prioritization to writing product requirements and delivering the roadmap with engineering.
Lead and expand core pillars within Cortex Cloud Identity Security by introducing innovative and disruptive approaches.
Proactively collaborate with cross-functional teams including engineering, sales, marketing, and customer success to ensure product alignment and successful launches.
Develop a deep understanding of cloud and identity security practitioners' needs and use cases to guide product strategy.
Define and execute go-to-market strategies by working closely with marketing and sales teams to effectively launch new features and solutions.
Support existing customers by identifying common user problems and ensuring the solutions you define meet their needs.