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We are a global fintech software firm at the forefront of providing state-of-the-art technology to the world's largest global banks and hedge funds. Specializing in ultra low-latency strategy and market data solutions, we are committed to delivering cutting-edge innovations to the Financial Industry. With a prominent Israeli R&D center in Jerusalem and development centers in Ukraine's Kharkiv and Dnipro, Fluent is a dynamic and collaborative environment. Project Manager is a market leader with a significant tier 1 & 2 client base in the financial world.
Responsibility will include
* Manage 2-3 project, each is a world-class customer
* Be responsible for customer communication, gathering requirements and managing delivery timelines
* Communicate and co-manage development and QA teams in Israel and Ukraine
* Present project status reports to management.

We are At Cross River, we're building the financial infrastructure that powers global innovation. With our cutting-edge suite of embedded payments, cards, and lending solutions, we enable millions of businesses and consumers to transact seamlessly and securely. With 900+ employees worldwide and an R&D center of over 160 employees in Jerusalem - we’re reshaping how financial technology is developed and delivered. .

The Role:
The Engineering Support team is dedicated to creating a positive onboarding experience for our customers. We guide them through the entire process - from initial setup to ongoing support. Our team combines technical expertise with business orientation to deliver a seamless and effective experience. This role requires Ability to work full time from Sunday to Thursday during US hours (15:00/16:00–24:00) with some flexibility

Who You Are:

* You’re a people person with a strong sense of empathy for customers.
* You can read situations, understand team dynamics, and take initiative to get things done.
* You’re tech-savvy with a developer’s mindset and business-oriented, ensuring a positive customer experience.
* You have a customer-first mindset, ensuring their needs and experience are always your top priority.


What You’ll Actually Be Doing:

* Support enterprise-level Partners and internal teams with technical onboarding and integration to our systems.
* Provide ongoing technical support, including troubleshooting, investigating error messages, resolving coding issues, and addressing errors related to system updates.
* Collaborate closely with internal departments such as Development, IT, NOC, Implementations, Operations, and Relationship Management.

Why You’ll Love Working Here:

* Flexible hybrid work model: three days a week at our Jerusalem office
* Monthly wellness reimbursement – from therapy to gel manicure, it's up to you
* Full Keren Hishtalmut, private health and dental insurance
* Volunteer days, donation matching, Yoga and Pilates
* A supportive, collaborative culture that puts our people first

Next Step:
Hit Apply!

join our Security Team. This is a flexible, part-time role with excellent conditions in a young, innovative, and dynamic work environment, perfect for combining work with studies.

What youll be doing
Work rotating shifts: 17:00-23:00, 23:00-08:00, including weekends (Friday-Saturday)
Respond to and manage security incidents and emergencies
Conduct routine patrols and security audits across company buildings
Monitor advanced security and surveillance systems
Provide assistance and support to employees and visitors

This isnt just another back-office BI role. data drives strategy. Youll work directly with product managers, designers, and engineers, using your analytical skills to shape key decisions, optimize user experiences, and lead experiments that have a direct impact on our product strategy and growth.

What you will be doing
Drive key product decisions by turning data into powerful insights that shape strategy
Partner with product teams to define goals, set metrics, and monitor performance
Shape product features and experiments with a data-driven perspective
Build dynamic dashboards that keep teams aligned on critical KPIs
Adapt quickly in a fast-paced environment to meet evolving needs
Act as a strategic partner to product leadership, surfacing key growth opportunities, identifying blind spots, and proactively recommending next steps
Collaborate closely with PMs, growth marketers, designers, and AI experts to bring data-driven thinking into every stage of the product lifecycle from ideation to post-launch evaluation

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

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.

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.

Required Intelligence Specialist
Jerusalem
Full time
About the team:
Our Intelligence Team was built in order to play a central role in shaping how the company navigates an increasingly complex and competitive global environment.
We track fast-moving trends, decode strategic shifts, and deliver insight that informs decision-making across product, strategy, policy, and executive functions.
Our work is dynamic, cross-disciplinary, and often ahead of the curve.
This is not a classic research role. We're looking for someone with a strong intelligence background who knows how to go beyond surface signals, connect disparate dots, and generate actionable insights with clarity and discretion.
Our mission is to detect trends and use those to evaluate risks or opportunities for us. Therefore, we are looking for someone who can anticipate future trends based on real-time developments.
The position requires on-site presence two days a week at our Jerusalem office and two days a week at our Tel Aviv office.
What Will Your Job Look Like?
Analyze the present and future landscape of the autonomous vehicle and mobility ecosystem, identifying key developments in technology, industry dynamics, and emerging players
Identify high-value information from unconventional sources, including conversations, events, and informal market signals
Translate fragmented or ambiguous inputs into concise, strategic briefs that inform decision-makers
Build and maintain stakeholder and ecosystem maps to support internal initiatives and long-term planning
Collaborate closely with product, strategy, and business teams to ensure intelligence is timely, relevant, and actionable.

The Operating System Team is looking for a highly talented Embedded SW Integration Engineer with a passion for operating systems and Linux in specific.
The team is developing the Boot and Operating System SW for our autonomous vehicle and smart advanced driver assist platforms.
What will your job look like?
Hands-on debugging and testing of OS and related components (Boot, HW initialization, Device drivers, Linux Kernel, User space libraries and tools & automated tests in python).
Deep understanding of the involved OS/Boot components and their integration with other SW/HW modules involving testing automation and system level validation.
Closely work with members of the Boot and OS development teams to integrate, test and automate new features, components and systems.
Release & feature management in a multi-project and multi-disciplinary environment while managing CI systems for testing coverage.

The Product Validation department is looking for a Validation Engineer.
Our department is responsible for delivering high-quality ADAS (Advanced Driver Assistance Systems) products.
We are the first line of support for our customers around the globe, and as our Validation Engineer, you will interact with most of our departments to achieve our goals.
What will your job look like:
Perform system-level validation of embedded systems, covering both hardware and software, with a strong focus on functional testing
Design and maintain test environments, including lab setups, test systems, and configurations.
Write and execute test plans and test cases based on system requirements, including manual and automated tests.
Validate communication protocols and system interfaces, and perform hardware bring-up and integration testing.
Install and support debug systems and sensors on development vehicles and assist automotive customers during integration.