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Required Solution Expert
Description
A leading provider of sales engagement and revenue optimization solutions, empowering businesses to streamline their sales processes and drive growth. As a company that advocates a customer-first approach, we're known for our professional Success team and are hiring a Solution Expert.
As a Solution Expert you will act as the technical trusted advisor for the customer and be responsible for building the solution and leading the onboarding process through implementation, configuration, and integrations.
You will also be responsible for configuring the software, answering questions, leading technical sessions and ensuring the client is satisfied with the solution. You'll work closely with Customer Success, Support, and Product teams, and will be the go-to person for any technical solutions. It's a great opportunity for those who are thrilled by the combination of customer-facing and technical and logical processes.

We are seeking a motivated MSc student to join our R&D team as a Machine Learning Engineer focusing on medical image processing (CT, MRI). In this role, you will support the development and optimization of deep learning models for image segmentation and analysis, leveraging U-Net and 3D U-Net architectures.
This is a hands-on opportunity to work on real-world clinical data and contribute to next-generation solutions for diagnostic and procedural planning workflows.
How you will make an impact:
Model Development:
Assist in designing and implementing deep learning models for medical image segmentation using U-Net, 3D U-Net, and nnU-Net frameworks.
Support optimization of models for volumetric CT/MRI datasets.
Data Handling & Processing:
Develop preprocessing pipelines (normalization, augmentation, resampling).
Integration & Experimentation:
Support integration of models into research pipelines using tools like MONAI and 3D Slicer.
Run experiments, evaluate model performance, and document results.
Collaboration:
Work closely with engineers, data scientists, and clinical teams.
Participate in technical discussions and contribute ideas for improving model performance.
Research & Innovation:
Stay updated on state-of-the-art methods in medical imaging AI and segmentation.
Explore improvements in model architecture and training strategies.

We are looking for a talented and passionate Full Stack Software Engineer to join our growing R&D team and help build next-generation data and AI-driven products.
In this role, you will take part in designing and developing scalable, high-performance web applications while working with modern technologies, advanced development methodologies, and cloud-native architectures. You will collaborate closely with Product, UX, QA, and fellow engineers to deliver exceptional user experiences and innovative solutions.
If you enjoy solving complex technical challenges, exploring new technologies, and working in a fast-paced environment where your impact is significant, wed love to meet you.
What Youll Do
Design and develop modern, scalable web applications from end to end.
Build robust backend services and APIs using modern server-side technologies.
Develop rich, responsive, and high-performance frontend applications.
Translate product and UX requirements into clean, maintainable, production-grade code.
Participate in architecture and technical design discussions.
Work with AI-powered technologies and modern data platforms.
Collaborate closely with Product Managers, UX Designers, QA Engineers, and other developers in an agile environment.
Continuously improve code quality, development processes, and engineering standards.
Explore and adopt new technologies, tools, and development approaches.
Who You Are
A fast learner who quickly adapts to new technologies and challenges.
Curious, innovative, and passionate about technology.
A team player who enjoys brainstorming and collaborative problem-solving.
Comfortable working with both modern and legacy systems.
Motivated to create impactful products with a great user experience.
Someone who thinks outside the box and brings creative solutions to complex challenges.

Required Software Engineer - Verification and Reliability
The Mission
We are building NeuralMesh- the worlds first intelligent, adaptive mesh storage system. To ensure our platform is unbreakable for the worlds largest AI and GPU clusters, we don't just "test" our code. We build an adversarial distributed system as complex and sophisticated as the product itself.
We are moving away from traditional QA automation. We are building a high-octane engineering force that treats reliability as a high-end software problem. We need "Quality Hackers" who want to build the technology that proves bugs don't exist.
In this role as a Software Engineer in Test (SET), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures - latency, packet loss, and hardware crashes - to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.

Required Senior Software Engineer, Filesystem
What you'll be doing:
The filesystem group is a high-powered team responsible for implementing algorithms at scales of 100s of PBs. The team also manages the core filesystem components, including blocks and metadata management, snapshots, RAID logic, object-store tiering, unique cloud disaster recovery features, and more. And most importantly, they skillfully handle the most delicate part of the solution - our customers data.
As a Senior Software Engineer, youll:
Design and develop distributed file system components to support data management features such as snapshots, replication, tiering, and advanced data reduction algorithms;
Participate in the design, architecture, and implementation of next-generation storage architecture;
Assist in technically managing initial storage implementations including proofs-of-concept;
Diagnose bottlenecks and implement clean and performant solutions to achieve unbeatable performance;
Design algorithms and data structures to make sure customer data is safe and coherent across our solution in a wide variety of failure modes; and
Constantly revisit the architecture, algorithms, and methodologies to improve productivity, reliability, and maintainability.

Required Senior Software Engineer, Control
As a Senior Software Engineer, youll:
You will be responsible for building the "brain" of our main product, which is a distributed file system -the layer that manages orchestration, metadata, cluster membership, and implements complex logic required to manage hundreds of thousands of nodes, for cluster scaling, automated failover, zero-downtime rolling upgrades and "self-healing" to detect and remediate hardware failures or network partitions.
Design, implement, unit test, and maintain services that coordinate and the cluster
Optimize Performance: Work with complex data structures like spanning trees or LSM-Trees, concurrency control mechanisms (MVCC) to improve speed and efficiency.
Collaborate closely with cross-functional teams to translate backend capabilities into real-world impact.

Required Performance Engineer
About the role;
Were building a next-generation platform for validating large-scale distributed systems. Our goal is to continuously ensure the correctness, performance, and resilience of the Data Platform across every layer of the stack.
As a Senior Software Engineer, youll work hands-on on the systems and frameworks that test, stress, and validate complex distributed infrastructure under real-world conditions. Youll help design and build automated environments that simulate scale, concurrency, and failure scenarios, and youll contribute to evolving how we ensure reliability and correctness in modern infrastructure systems.
This role is ideal for engineers with a strong distributed systems background who enjoy deep technical problem-solving, working close to the system, and building tools that improve quality, stability, and confidence at scale.
What Youll Do:
Design and implement core components of a distributed testing infrastructure and quality platform.
Build automated frameworks to validate functionality, performance, and resilience at scale.
Collaborate closely with infrastructure, storage, and platform teams to ensure quality is built into the development lifecycle.
Contribute to improving tooling, test coverage, and engineering best practices across the organization.

Required Research Scientist - Audiovisual Understanding, Model Foundations
Team & role
The Core Generative AI team is a unified group of researchers and engineers dedicated to developing our generative foundational models that serve LTX Studio, our AI-based video creation platform. Our focus is on creating a controllable, cutting-edge video generative model by merging cutting-edge algorithms with exceptional engineering. This involves enhancing machine learning components within our sophisticated internal training framework, crucial for developing advanced models. We specialize in both research and engineering that enable efficient and scalable training and inference, allowing us to deliver state-of-the-art AI-generated video models.
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.

Required Research Scientist - Audiovisual Generation, Model Foundations
The role
Following the success of LTX-2, our widely adopted open-source text-to-audio+video model, we are expanding our efforts to develop cutting-edge audio+video generation models and are hiring Research Scientists to join our LTX-2 Core team.
Weve been at the forefront of innovation in text-to-image and text-to-audio+video generation, with LTX-2 driving our flagship product, LTX Studio, and gaining significant traction in the research and open-source communities, including integrations with platforms like ComfyUI and Diffusers.
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.

Required Research Scientist - LTX Model Evaluation
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.

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.

abra is seeking for an Senior FPGA Engineer This role require close collaboration with multidisciplinary teams, including hardware, software, verification, and system engineers, to deliver high-performance, mission-critical FPGA solutions—from concept and design through development and production, all the way to integration and operational deployment. Full-time position, Sunday–Thursday, in Holon.

our company is a leading hybrid cloud security company revolutionizing the way organizations manage cyber risk. We provide cutting-edge exposure management solutions by simulating real-world attack paths across cloud and on-prem environments. Our technology identifies misconfigurations, vulnerabilities, and identity exposures, allowing organizations to remediate risks with minimal effort.
We are looking for a motivated SRE Intern to join our Site Reliability Engineering team in a part-time capacity. This is an exciting opportunity to gain hands-on experience operating large-scale, multi-cloud production infrastructure that powers a real cybersecurity product. You'll work alongside experienced SREs on the systems and automation that keep our platform reliable, observable, and secure. Responsibilities: Help build and maintain automation and tooling that improve the reliability and operability of our production environments Work with Kubernetes and multi-cloud infrastructure (AWS / GCP / others) under the guidance of senior engineers Contribute to our observability stack - dashboards, alerts, and monitoring - to help us detect and understand issues faster Write scripts and small services ( Python / Go / NodeJS) to automate operational tasks and reduce manual work Participate in investigating and resolving production issues, learning real-world incident response and troubleshooting Collaborate with developers and SREs across the team to ship and operate changes safely