דרושים » תוכנה » NLP data Scientist (Conversational AI)

As a Senior Data Scientist on our Applied AI team, you will join our Tel Aviv office and play a hands-on, end-to-end role in delivering innovative capabilities that help mayors and other city leaders understand their communities and improve the lives of millions worldwide. Reporting to the Applied AI Team Lead, you will collaborate with product, engineering, and fellow data-science teammates to turn cutting-edge research into production-ready solutions-quickly, reliably, and with maximum real-world impact. Youll work with a rich mix of data sources (including social media, news stories, survey results, resident feedback, and more) to create models and AI-powered features that scale.

Day to Day

Design, build, and deploy AI and machine-learning solutions, from data exploration through modeling, evaluation, and integration into customer-facing products and internal tools.
Optimize models for quality and scalability through feature engineering, hyper-parameter tuning, runtime profiling, and thoughtful architectural choices.
Build and maintain data pipelines using tools such as Airflow, Spark, and Databricks to ensure clean, reliable inputs for downstream models.
Collaborate closely with product managers, engineers, and designers to refine problem statements, iterate rapidly, and ship impactful features on schedule.
Champion technical excellence by conducting code reviews, sharing best practices, and mentoring teammates across data science and engineering.
Stay current with the latest developments in AI-including LLMs, RAG systems, and AI agents-and proactively propose ways to incorporate new techniques into our workflows.
Work an in-person or hybrid schedule, spending at least three days per week in our Tel Aviv office.

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.

Required Data Science Engineer
About the Team
Our team focuses on delivering cutting-edge, AI-powered automated application security features within our ASPM product. We are a dynamic, agile team emphasizing seamless transitions from design to production, deployment, and ongoing monitoring. We excel at operationalizing machine learning, data science, and AI solutions into robust, secure, and high-performance security capabilities.
What You Will Do
Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, MLOps specialists, and analysts.
Design, build, and optimize end-to-end AI-driven features - from experimentation and model training to validation and deployment.
Develop production-grade code (Python and C#) to integrate advanced models and data-driven capabilities into our core products.
Continuously evaluate model performance and data quality in real-world settings, proactively driving improvements, retraining, and robust monitoring.

We are seeking a Product Manager for AI Platform, to lead most critical evolution: the transformation to an Agentic Platform.

This role operates as a "Startup within a Startup." You will own the end-to-end AI domain, from building the underlying technical infrastructure to launching the interfaces our customers interact with.

You will drive the entire product lifecycle: bringing innovative ideas to the table, executing on early versions, and collaborating closely with internal teams and design partners to validate value. Your ultimate goal is to mature these capabilities from early concepts into core platform standards, driving mass adoption across our entire user base.

You will serve as the knowledge center for the organization, guiding how the entire platform must evolve to support the next generation of autonomous engineering.

What You Will Be Doing

Lead AI product domain from ideation to launch of customer-facing AI interfaces and agents
Design and manage AI Agents platform, enabling customers to create, manage, and run AI agents
Drive ecosystem initiatives to make the platform native to agents through API improvements, MCP integration, and agent-accessible protocols
Define strategic direction for making "AI-Native," guiding data architecture for effective AI agent interaction
Own product roadmap and prioritization, balancing immediate needs with long-term Agentic architecture investments
Advocate across product and R&D teams to integrate AI-native interfaces and drive AI-first development mindset
Identify high-impact opportunities through customer discovery and experimentation with cutting-edge AI technologies
Collaborate with engineering and design to translate AI capabilities into intuitive, trust-building user experiences
Analyze adoption metrics and feedback to optimize AI performance and increase trust in autonomous workflows
Act as company AI center of excellence, enabling Sales, Marketing, and CS teams to articulate Agentic Engineering value

Required Machine Learning Engineer II - GenAI Applications
26947
About the team:
This opening is for the GenAI Applications Team within the Data & AI Marketplace department.
The GenAI Applications team is responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and trip helpfulness. The team builds AI-driven applications and conversational agents, such as chatbots and intelligent assistants, that significantly enhance the end-to-end customer experience.
Role Description:
As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

We are looking for a talented AI Applied Researcher to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.

What Youll Do

Lead an applied research for AI-driven features in the platform
Research and optimization agentic flows to solve complex problems
Collaborate with engineering teams to design, build, and maintain production pipelines
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

We are looking for a highly motivated candidate to join our Data Science team - If you are passionate about NLP \LLMs and have 4+ years in the field, this is for you!

We are a leading innovator in the financial compliance space, serving some of the worlds largest banks and financial institutions. As a Senior Data Scientist, youll be at the forefront of this critical mission - to help these organizations meet regulatory obligations by monitoring vast volumes of employee communications.

Our team is responsible for developing advanced NLP\LLM based solutions that can detect rare and subtle indicators of suspicious behavior hidden within massive streams of unstructured text. This is a high-impact role that requires balancing accuracy, scalability, and cost-efficiency in a production environment.

What Youll Do:
Lead data science project E2E: Research, experiment, develop and productize advanced NLP, LLM and autonomous agent solutions in various domains such as classification, summarization, translation, information retrieval and AI assistant.
Use advanced deep learning and large language models, to enhance our ability to find the needle in a haystack in the world of structured & unstructured data of financial electronic communication.
Conduct rigorous experimentation, analysis, and optimization to ensure performance, efficiency, and scalability.
Develop processes, tools and frameworks to monitor and analyze model performance and data accuracy.
Innovate, develop, and test state-of-the-art approaches to solve our challenging problems: domain adaptation, fine-tuning, prompt engineering, zero- and few-shot learning, autonomous agents, using open and close large language models.
Assist and mentor other team members in the implementation and research.
Collaborate closely with domain experts, product and engineering teams to translate research breakthroughs into scalable commercial products.
Identify the latest technology to improve our AI capabilities in a variety of languages and help shaping our AI roadmap.

As a Data Science Team Leader at our company, you will lead a high-performing team developing AI/ML solutions that secure the digital worlds most sensitive assets. Youll play a key role in driving innovation, productizing machine learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges. In this leadership role, youll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. Youll work closely with data scientists, engineers, analysts, product managers, and Cyber-Security researchers to build intelligent features across our companys identity security portfolio.
Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
Champion best practices in MLOps, data governance, explainability, and monitoring.
Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

Required Senior Machine Learning Scientist I - GenAI Applications
26992
About the team:
This opening is for the GenAI Applications Team within the Data & AI Marketplace department.
The GenAI Applications team is responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and trip helpfulness. The team builds AI-driven applications and conversational agents, such as chatbots and intelligent assistants, that significantly enhance the end-to-end customer experience.
Role Description:
As a Senior Machine Learning Scientist, you will work closely with engineers and to design, develop, and evaluate machine learning solutions for scalable, customer-facing GenAI applications. Your work will focus on researching, training, fine-tuning, and rigorously evaluating models leveraging LLMs, recommendation systems, and agent-based architectures, using state-of-the-art techniques. You will drive experimentation, define success metrics, and translate insights into impactful AI solutions that shape the future of intelligent travel products.
Key Job Responsibilities and Duties:
Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning), build algorithms, and engineering approaches to drive business impact..
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate models performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.