לוח משרות דרושים NLP/Machine Learning

Following the success of LTX-Video, our widely adopted open-source text-to-video model, we are expanding our efforts to develop cutting-edge video generation models and are hiring Research Scientists to join our LTX-Video Core team.
At our company, weve been at the forefront of innovation in text-to-image and text-to-video generation, with LTX-Video 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 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-video generation.
Collaborate with data engineers to curate and preprocess text and video data.
Optimize models for high performance, ensuring efficiency in training and inference phases.
Build new controls and capabilities into generative text-to-video models.
Stay updated with the latest developments in Generative AI, particularly in the field 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.

The Core Generative AI team at our company Research 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 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 deeply understanding supercomputer performance. 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/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.

We're seeking a Developer Advocate to build and nurture the developer community around our open-source model, LTX Video. This role sits at the intersection of technical development, community engagement, and product strategy, requiring someone who can speak the language of developers while fostering meaningful connections within the AI community.
What you will be doing
Establish and manage community presence across key platforms including Discord, GitHub, Hugging Face, and Reddit
Create and moderate technical discussions around model development, implementations, and fine-tuning
Organize and host AMAs (Ask Me Anything) sessions and other educational webinars
Build and maintain relationships with key community members and developers
Identify and recruit beta testers for new features and implementations
Program Management
Develop and manage a community sponsorship program for outstanding contributors
Create documentation and resources to support community development efforts
Track and analyze community metrics and engagement
Establish best practices for community contribution and collaboration
Coordinate with internal teams to align community initiatives with product roadmap.

shaping the Cognitive Banking era, harnessing AI to help banks anticipate customer needs, provide actionable insights, and deliver intelligent financial guidance. Our platform continuously analyzes and leverages real-time transactional data, enabling banks to proactively support customers in managing their finances and reaching their goals. As industry leadersyes, we really are leaderswe partner with the worlds top financial institutions, empowering over 150 million customers monthly across 35 global markets from offices in New York, London, Singapore, São Paulo, and Tel Aviv.
About the position
We are seeking an experienced Data Scientist to advance cutting-edge Machine Learning (ML) & Deep Learning (DL) research, champion Responsible AI best practices, and drive product innovation. This role offers the opportunity to develop and optimize ML models while also pioneering innovative AI applications under strict governance and ethical standards. Youll work on both structured, production‑ready AI systems and experimental, next‑generation AI solutions, adapting based on business needs.

If you love rigorous ML development, creative AI prototyping, AND ensuring AI is built responsibly, this is the perfect role for you!

Responsibilities
ML/DL Research & Applied Data Science
Develop, optimize, and deploy ML/DL models aligned with business goals.
Conduct data exploration, preprocessing, and model enhancement to improve performance.
Implement robust model monitoring pipelines to ensure reliability and mitigate drift.
Collaborate with engineering & product teams to integrate AI solutions into production systems.
New Product & Backlog Research
Scout emerging technology trends and conduct market & internal backlog research to surface unmet customer needs.
Evaluate and prioritize research findings, translating them into actionable, data‑driven proposals that influence the product roadmap.ש

Required Intern, AI Science
Responsibilities
How youll contribute:
As an AI Scientist Intern, you will have the opportunity to apply and grow your skills in natural language processing (NLP) and large language models (LLMs).
You will work with diverse, multi-modal data types at a massive scale, leveraging proprietary data to help unlock insights.
This role will provide you with hands-on experience in advanced model fine-tuning, transfer learning, prompt engineering, few-shot learning, and data augmentation methods to build both predictive and generative
models, fueling innovation across our products.
You will collaborate with our cross-functional teamsincluding data engineers, ML architects, product managers, and business analyststo support the development of high-performance LLM pipelines.
You will assist in designing and executing research strategies for optimizing model architecture, prompt optimization, tokenizer customization, data curation, noise reduction, and hyper-parameter tuning to meet our complex and large-scale data challenges.
Under the guidance of senior team members, you will help provide stakeholders with an understanding of how to utilize LLM models, embeddings, and vector databases to meet critical business needs.
You will also have the chance to contribute to projects that are at the forefront of advancements in generative AI, reinforcement learning, and self-supervised learning.
This internship will immerse you in the end-to-end development of LLM workflows, from hypothesis generation and model fine-tuning to data preprocessing and A/B testing.
You will be part of a continuous feedback loop for model retraining and precision tuning, ensuring alignment with shifting data scales and complex multi-domain applications.
You will also learn to use interpretability tools to understand LLM outputs and contribute to a team that is focused on maximizing the impact of cutting-edge AI capabilities.

We are looking for a Senior ML Engineer.
As a Senior ML Engineer , you will lead the design, deployment, and maintenance of production-ready machine learning systems that power legal insights at scale. Youll work across disciplinesintegrating LLMs, building pipelines, and optimizing infrastructureto deliver real-world impact.
Youll gain full ownership over the systems you build, from selecting the tools and platforms to deploying services in production. Youll work closely with DevOps and Data Engineering to ship robust solutions that drive meaningful change in the world.
Responsibilities :
Design and implement production-grade ML systems, including APIs, batch jobs, and streaming pipelines using Databricks, MLflow, AWS/GCP.
Build and manage ML infrastructure, including data pipelines, model training, deployment, and monitoring.
Develop and maintain end-to-end ML/LLM pipelinesfrom data ingestion and labeling to synthetic data generation, model registry, and rollout.
Own and improve MLOps practices: automated testing, CI/CD, monitoring, alerting, and model governance.
Write clean, maintainable Python code and uphold best practices in engineering and documentation.
Collaborate with DevOps and Data Engineering teams to scale systems and improve performance.
Research and recommend the best tools, platforms, and practices to support ML at scale.

Join as the first engineer and researcher behind GenAI Protect, building LLM-powered discovery, classification and policy-enforcement services that secure enterprise generative-AI usage.
Key Responsibilities
Design and implement scalable inference services (Python/FastAPI, Triton, ONNX) with GPU orchestration.
Develop and fine-tune transformer models for prompt inspection, PII/red-flag detection and intent analysis.
Collect datasets, build evaluation pipelines and drive continuous model improvement.
Collaborate with Threat-Intel and Product to respond to emerging GenAI attack vectors.
Publish internal/external tech blogs; help hire and mentor future AI-security engineers.

We are seeking an exceptional Data Scientist to lead applied research in machine learning and drive the AI transformation . This pivotal role will shape the next generation of customer-facing products and internal tools, helping to redefine the trading experience through advanced AI.
Key Responsibilities:
Design and build end-to-end AI workflows including synthetic dataset generation, data preprocessing, model development, deployment, and agent orchestration.
Design and implement LLM (Large Language Model) evaluation frameworks to assess new AI models, techniques, and parameters.
Process and analyze large-scale structured and unstructured data from databases, APIs, and develop machine learning models for time series forecasting, regression, and classification tasks.
Design and implement enterprise-grade RAG systems using LLMs, vector databases, GraphRA, G, and intelligent agents.
Optimize AI-user interactions through advanced prompt engineering and retrieval strategies.
Translate cutting-edge AI research into practical, scalable tools for internal and customer-facing applications and collaborate with global and cross-functional R&D teams to drive innovation across product lines.
Apply MLOps and LLMOps best practices to ensure robust model training, deployment, and monitoring pipelines.

We're looking for a Director of Engineering, Platform our company's ML to lead the engineering teams responsible for the core infrastructure, multi-cloud capabilities, and developer tooling behind our rapidly growing ML product line. This is a great opportunity to build and scale high-performance platform engineering in the context of cutting-edge ML software all with the stability, reach, and resources of our company behind you.
In this role, you will.
Lead and scale a high-impact group responsible for our company MLs core platform, infrastructure, developer productivity, and tooling.
Own and evolve multi-cloud architecture and services, ensuring reliability, scalability, and performance across AWS, GCP, and Azure.
Drive technical strategy and execution for platform components that serve as the foundation for all ML features and workflows.
Collaborate closely with Product, Security, and Customer Success to deliver enterprise-grade, compliant, and secure solutions.
Champion developer experience and internal tooling, creating a highly productive and enjoyable environment for engineers company-wide.
Recruit, mentor, and grow a team of passionate engineers and managers focused on technical excellence and speed of delivery.
Foster a culture of bold ownership, radical accountability, and a desire to win big.

Were hiring a Machine Learning Engineer to accelerate AI-driven innovation across our B2B SaaS product and the broader organization.
This is a hands-on, end-to-end development role where you'll lead the implementation of ML/LLM-based solutions that boost operational efficiency and deliver exceptional product experiences. As an AI-First company, we embed AI across every department and workflowyou'll be at the heart of this transformation.
You will collaborate closely with product managers, engineers, and stakeholders to identify impactful AI opportunities, build state-of-the-art systems, and scale them across the organization.
What You Will Do:
AI-First Development: Design and implement POCs and production-ready ML/LLM solutions that address real-world business problems.
End-to-End Execution: Own projects from research through deployment, including model training, evaluation, integration, and monitoring.
Tool Evaluation: Stay current with state-of-the-art ML/LLM tools and frameworks (e.g., LangChain, Hugging Face Transformers, TensorFlow, PyTorch) and recommend their application.
Collaboration: Partner with engineering, product, and operations teams to embed AI into user-facing features and internal workflows.
System Integration: Build scalable microservices and APIs to deliver AI capabilities across the product.
Operationalization: Contribute to DevOps practices for CI/CD, observability, and ongoing optimization of AI models.
Strategic Reporting: Communicate progress and insights directly to senior management.

We are seeking a Senior Data Scientist to lead the development of personalization models that power our AI agents. In this role, youll design and deploy intelligent systems that understand each travelers preferences, intent, and behaviortransforming complex user journeys into effortless, hyper-personalized experiences.This is a high-impact, cross-functional role working closely with product managers, engineers, designers, and the AI/LLM platform team to create deeply personalized, autonomous travel assistance that feels like magic (but is all math and modeling underneath).
What Youll Do:
Design and build machine learning models that power personalization across our agentic platform, including traveler profiles, flights & hotels recommendation engines, and behavioral prediction systems.
Develop algorithms that adapt and learn from user behavior over time, channels, and modalities (text, voice, action).
Collaborate with PMs, engineers, and conversational designers to integrate ML into real-time decision loops, conversational agents, and proactive UX flows.
Own experimentation pipelines and performance evaluation, AB tests, offline metrics, and production agent behavior.
Work hands-on with structured and unstructured data (e.g., travel history, chat logs, user feedback, booking behavior) to extract insights and drive model improvement.
Define and maintain robust MLops practices: monitoring, retraining, feature pipelines, and real-time inference.
Stay current with the latest in recommender systems, LLM integration, embeddings, retrieval augmentation, and agentic reasoning to continuously evolve our approach.

We are seeking a sharp, execution-focused AI Group Manager to lead growing teams of data scientists, data analysts, and clinical experts. This group is central to our mission transforming rich behavioral health data into meaningful, explainable, and scalable AI-powered capabilities.
Youll be responsible for shaping and executing our AI strategy, with a strong focus on large language models (LLMs) and their deployment in real-world clinical settings. Your team will balance rapid innovation cycles with rigorous delivery of production-grade AI systems embedded into the platform.

At our company, were reinventing DevOps and MLOps to help the worlds greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust our company to manage, accelerate, and secure their software delivery from code to production - a concept we call liquid software. Wouldn't it be amazing if you could join us in our journey?
Are you a platform engineer who thrives on designing and building scalable, high-quality services and infrastructure?Do you want to work on cutting-edge services while shaping the backbone of an ML platform? If so, wed love to have you join our company's ML our MLOps group.
As a Senior Platform Engineer, you will play a critical role in architecting and developing cloud based core services and infrastructure with a strong emphasis on clean code, performance, observability, monitoring, and security. This role also includes developing core Go/Java libraries, cross-cutting services like authentication and authorization, Kubernetes deployments, billing etc.You will collaborate closely with engineering teams, DevOps, architects, and product managers to ensure a scalable, stable, and high-performing system.
As a Platform Engineer at our company's ML you will...
Write clean, maintainable, and efficient code following best practices.
Design and develop robust backend services with scalability, performance, and security in mind.
Conduct high-quality code reviews and architecture discussions, ensuring best practices are followed.
Take full ownership of projects - from ideation and design to production deployment and maintenance.
Collaborate with cross-functional teams to define, design, and ship new features.
Stay current with industry trends, technologies, and best practices in software development and cybersecurity.
Be involved in multiple aspects of an ML platform - from data sources to inference pipelines.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

We are looking for a Senior Data Scientist with deep expertise in Large Language Models (LLMs), Deep Learning, and Neural Networks to join our Threat Research group, located in our Tel Aviv Office. Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for new products, and drive innovation and thought leadership in cybersecurity.
Key Responsibilities :
Serve as the technical lead for projects involving LLMs, deep learning, and neural networks focused on cybersecurity applications.
Design, train, fine-tune, and deliver LLMs and advanced deep learning models for tasks such as anomaly detection, threat classification, and automated analysis of security data.
Drive hands-on research from ideation through prototyping to scalable production systems.
Collaborate with product and engineering teams to integrate advanced AI models into security solutions.
Analyze complex, high-dimensional security data (including text, logs, network traffic, and more) to identify emerging threats and attack patterns.
Mentor and guide other data scientists and contribute to the teams technical growth.
Represent in the AI and security communities through thought leadership, publications, presentations, and patents.