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Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.
So, what will you be doing all day?
Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark

we are looking for a Senior Analytics Engineer.
On a day-to-day basis, we transform raw data into clean, structured models using tools like SQL, Python, and dbt. We build and maintain modern BI platforms, develop reporting systems, and design AI-driven analytics that surface valuable insights quickly and reliably.
Our team is hands-on with building reusable metrics, defining source-of-truth data models, and ensuring consistency through a strong semantic layer. Whether were shipping a new dashboard, debugging a dbt model, or refining how a metric is defined across the business, our focus is always on clarity, scalability, and enabling smarter, faster decisions.

As a Software Engineer on our team, you'll architect and build high-performance backend systems that operate at the scale and precision demanded by our most advanced hardware platforms. Your work will directly shape how engineers, developers, and users around the world interact with complex hardware - making the powerful feel effortless.

You'll also be at the forefront of integrating AI-powered tools into our internal macOS applications, bringing intelligent capabilities to the people who build our next generation of products.

Design, implement, and optimize high-performance backend systems that manage the scale and complexity of advanced hardware.
Build and integrate AI-driven features into internal macOS native applications.
Abstract intricate hardware behaviors into clean, developer-friendly interfaces and APIs.
Work closely with external SW Engineers vendors, aligning on technical requirements and integration strategies.
Collaborate with a globally distributed team of engineers, designers, and end users to deliver impactful solutions.
Own the full development lifecycle - from architecture and design through implementation, testing, and deployment.
Contribute across a modern tech stack: Swift, C++, and Python.

Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.

Required Software Engineer III, Data and AI Infrastructures, Waze
Tel Aviv, Israel
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The team manages all engineering infrastructure for Waze data scientists, including: GenAI frameworks for internal applications and analytics (DataWhiz), evaluation frameworks for user-facing features, and MLOps for training and deploying ML models at scale. Additionally, the team oversees data pipeline infrastructures, infrastructure as code, and the application of engineering best practices within data science.
Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.
Responsibilities
Add new features to our GenAI analytics agents serving all of Waze for any data analytics questions.
Research in GenAI for ML research and exploration, backend GenAI models evaluation framework.
Understand ML or Data Science to have knowledge of the users of the framework.

we are looking for a Senior Machine Learning Engineer to work on LLM-based systems with a strong emphasis on integration, end-to-end workflows, and production readiness. This role combines performance optimization (prefill/decode, throughput, latency) with hands-on work integrating components across the AI platform.
A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.
***This is not a Data Science position***
Responsibilities:
Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure)
Design, implement, and optimize LLM inference workflows, including prefill and decode stages
Improve system performance with focus on throughput, latency, and interactivity
Write production-grade components in Python and integrate them into the broader system
Contribute to system-level logic such as smart hardware selection and execution strategies
Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines

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 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 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.

Were looking for a highly skilled Full Stack Developer to join our engineering team. In this role, youll design, develop, and maintain both backend and frontend systems that power our production and internal applications. Youll work across teams to deliver user-facing features end to end, building scalable, high-availability solutions that support production environments and future web-based platforms.
What will your job look like?
Design, develop, and maintain scalable backend services primarily using Node.js (and Python where applicable), applying modern web frameworks and industry best practices.
Build rich, responsive user interfaces using React, Angular, or Vue.
Develop end-to-end features, integrating frontend and backend components into cohesive, production-ready solutions.
Design and manage databases (SQL and NoSQL), focusing on performance, reliability, and solid data modeling.
Support and enhance production applications, ensuring high availability, resilience, and smooth operation across environments.
Build, containerize, and deploy applications using Docker and Kubernetes in Linux-based setups.
Implement and maintain CI/CD pipelines using GitLab CI for automated testing, integration, and deployment.
Work with AWS services to deploy, monitor, and scale cloud-based applications.
Contribute to system architecture, participate in code reviews, and mentor junior developers when needed.
Collaborate closely with product, design, and cross-functional engineering teams to deliver high-quality user experiences.

Were looking for a hands-on Business Systems & Automation Specialist to join our growing team. In this role, youll manage and optimize the business applications and integrations that power Candexs operations.
Youll be part of the team that owns the companys applications ensuring theyre well-maintained, scalable, and integrated to support business growth.
Youll be one of the go-to experts for building automations and workflows to streamline operations across departments such as Sales, Customer Success, Operations, etc...
Responsibilities:
Administer and maintain core business systems and SaaS tools.
Design, build, and manage automations, native integrations, and custom API scripts.
Partner with cross-functional teams to understand business requirements and translate them into efficient system solutions
Explore, test, and implement new technologies or integrations that can add value to the business.
Manage CRM configuration, data integrity, and automations to support sales and account management workflows.
Monitor system performance, troubleshoot issues, and ensure optimal reliability.
Identify opportunities to improve processes through technology and automation.
Document system configurations, workflows, and best practices.
Collaborate with IT & security to ensure compliance and secure integration across tools.