לוח משרות דרושים הייטק תוכנה

As the ML Platform Tech Lead, youll be responsible for the development of AI infrastructure, taking an active role in mentoring backend engineers directly.

This is a hands-on tech- lead position that blends system design and technical strategy. You will be expected to work closely with our ML research teams, product, and engineering stakeholders to take cutting-edge AI models into production, powering features across our creative apps used by millions worldwide.

You will own the full development lifecycle, from system architecture through deployment and operation, while also being accountable for team delivery, collaboration, and growth.

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.

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 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.

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 the 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

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 the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust our company to help secure their most critical assets.
job description
we are looking for a staff software engineer to join our elite team which is building one of our strategic products for cloud security.
in this role, you will take part in building a new innovative product, and have a huge influence on its design, capabilities, and technology. you will have to demonstrate high professional skills, fast technology adoption, and the ability to work on aws. you will practice all software development life cycle in an agile oriented environment while exploring new technologies and tools to keep us using cutting edge solutions.
as a staff engineer, you will also lead and own various activities in the team while ensure high standers of quality and architecture best practices.

we are 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 talented experienced and passionate engineers to join us as a senior software engineer at the credential provider group.
you have the opportunity to join a new team which is working on the development of a popular product using various programming languages and technologies.

we are looking for a talented and experienced r&d platform engineer to join our dynamic team. our organization provides cutting-edge services utilized by both internal cyberark services and external customers. the ideal candidate will be responsible for defining and implementing best practices that can be shared across the company and working on edge technologies on the cloud. this position encompasses all stages of the software development life cycle (sdlc), including design, development, testing, and ensuring high roi on deliverables.
define and implement best practices for the r&d platform.
collaborate with internal and external stakeholders to understand requirements and deliver high-quality solutions.
work on edge technologies and cloud platforms to enhance our services.
participate in all phases of the sdlc, including design, development, testing, and deployment.
ensure high roi on deliverables by optimizing processes and solutions.
share knowledge and best practices across the company to promote a culture of continuous improvement.

we are 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 QA architect to join our elite team, contributing to the development of one of our strategic products for cloud security. in your role, you will be responsible for developing and maintaining high-quality work procedures, leading the team to achieve better quality. you will be involved in the full feature lifecycle - from gathering requirements with the product team to release - ensuring quality at every stage, including bug management and observability and defining QA work procedures, guidelines, and designing the entire testing process. the ideal candidate will be responsible for leading quality activities across solution-level features, ensuring the highest standards of quality are met. this role requires a proactive individual with excellent leadership and communication skills, capable of driving quality initiatives and fostering a quality-focused mindset within the organization. responsibilities: comprehensive understanding of the product's functionality, target use cases, and the value it delivers to customers. lead the quality efforts across multiple interfaces with a proactive and assertive approach, serving as the key point of contact for all quality-related matters. define, implement, and manage QA processes, promoting a quality-driven culture and managing the quality backlog. define the overall testing strategy and tooling stack across integration, regression, and load/performance testing. drive an automation-first approach - collaborating with developers to ensure code is testable and observable. lead root-cause analysis for escaped bugs and define improvement actions. own ci quality metrics and dashboards (e.g., build stability, TEST flakiness, regression coverage). influence decisions regarding TEST environments, mocks, TEST data, and production parity. collaborate with the centralized quality group to ensure e2e TEST coverage. quality point of contact: serve as the primary point of contact for quality-related matters concerning the unit or the cross-group feature.

Required Development Team Lead
- Lead and manage a cross-functional team (Mobile, Backend, IoT Cloud, DevOps), fostering technical excellence and professional growth
- Own the end-to-end Agile lifecycle - planning, prioritization, and execution - ensuring timely delivery of value
- Leverage emerging technologies to solve complex operational challenges and improve business efficiency
- Translate business requirements into scalable technical plans in close partnership with stakeholders
- Oversee backend, cloud, DevOps, and infrastructure domains to ensure stability and successful delivery.

company description
we are the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust us to help secure their most critical assets. to learn more about us , visit our blogs or follow us on x, linkedin or facebook. job description
we are looking for a bright, talented senior devex platform Developer to join a team of highly energized and professional engineers working on mission-critical systems in the red-hot cybersecurity industry. this role is focused on development flow productivity and building application infrastructures and tools to handle the challenges of hyper-growth and application scale.
you will design, implement, and deploy products and infrastructures that directly increase our stability and quality while reducing our time to market.
what you will do:
Developer platforms: design and develop solution-oriented enterprise DevOps platforms and tools to improve the Developer experience.
velocity & quality: create solutions to increase r&d velocity, reduce lead time, and improve overall product quality.
saas infrastructure: plan, design, and develop company's saas infrastructure, operation engine, and deployment strategy.
ci/cd & security: develop and adopt new technologies to improve ci/cd pipelines, utilizing a devsecops "shift left" approach to introduce security early in the cycle.
troubleshooting: perform platform and service troubleshooting across various applications, domains, and platforms.

we are the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust our company to help secure their most critical assets.
job description
as a staff engineer in the data & ai platform group, you will be a senior technical leader responsible for driving the design, implementation, and delivery of complex, high-impact features across our data and ai ecosystem. you will set engineering standards, lead cross-team initiatives, and provide hands-on technical guidance to developers working on large-scale, cloud-native distributed systems.
this role combines deep technical expertise with leadership: shaping the platforms architecture, mentoring senior engineers, and ensuring technical excellence and execution. in this role you will
lead end-to-end development of high-priority, cross-team features and initiatives in the data & ai platform. design and implement scalable, resilient, and secure distributed systems in a modern cloud environment. drive technical decision-making, influence architecture directions, and collaborate closely with product, data engineering, and ai teams. mentor developers, support their growth, and elevate engineering practices across the group. promote engineering excellence through code reviews, design reviews, and continuous improvement initiatives. evaluate new technologies and guide their adoption where appropriate. collaborate with engineers and managers across our company to align standards, share knowledge, and lead technical deep dives