דרושים » תוכנה » NLP Team Lead

We are seeking an experienced and visionary Head of Research to lead, shape, and advance the future of AI innovation across the organization. In this role, you will own the research strategy end-to-end - from long-term roadmap design to hands-on exploration, and guide a multidisciplinary team of NLP research engineers and linguists toward breakthroughs that elevate our core medical coding engine.
You will play a key role in the company, balancing exploratory research with high-impact product delivery. You will partner with Product, Engineering, and executive stakeholders to identify strategic opportunities, drive prioritization, and translate research capabilities into real-world outcomes at scale.
Responsibilities:
Manage and mentor a multidisciplinary research team while driving both technical excellence and personal growth.
Define the long-term research roadmap aligned with product and business objectives.
Lead the full research lifecycle, from ideation and feasibility studies to experimentation, evaluation methods, and production-ready delivery.
Evaluate and introduce new research capabilities and emerging trends such as LLM-based reasoning, semantic/graph modeling, hybrid rule-learning, and other frontier techniques.
Continuously track scientific trends to maintain a state-of-the-art research practice.
Collaborate closely with Product and Engineering teams to translate domain challenges into algorithmic solutions with measurable product impact.
Represent the Research function at leadership forums, communicate priorities and outcomes, and align stakeholders around research strategies and milestones.

Were hiring a Machine Learning Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of ML engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

Our data science team is seeking a highly skilled AI researcher with expertise in modern AI methods (e.g., multi-agent architectures, reinforcement learning on LLMs) and a passion for transforming theoretical challenges into real-world products.
In this role, you will leverage our unique clinical datasets to design and build groundbreaking solutions that provide medical benefits to millions of people. You will take full end-to-end ownership of your models - from ideation and research to production deployment and ongoing monitoring.
Working across both research and production environments, you should have proven experience in developing and deploying machine learning algorithms, along with strong interpersonal and collaboration skills. We value independent thinkers who are also proactive doers.

What Youll Be Doing:
Develop clinical AI models to support Ks clinic workflows, with a focus on patient-facing applications
Design and implement scalable, efficient pipelines for data preprocessing, information extraction, and model training
Stay up to date with the latest AI research and best practices, and translate them into production-ready solutions
Communicate complex technical concepts and solutions to non-technical stakeholders
Collaborate with MLE and AI engineering teams to deploy scalable, robust solutions

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.

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.

Required Machine Learning Scientist II - GenAI models and applications
21539
Role Description
Leadership/Team Quote:
The Content Intelligence team builds the platform that processes millions of images and texts daily, enriching our catalog with advanced machine learning models for content understanding, classification, and personalization. These capabilities power smarter recommendations, improved search experiences, and intelligent chatbots and agents that enhance customer interactions. The team also plays a key role in the AI Trip Planner, a new Generative AI-driven project transforming how travelers plan their next vacation
Role Description:
As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
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.

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.

Were hiring a ML Engineer to accelerate AI-driven innovation across Stamplis B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across Stamplis product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.

In this role, you'll be responsible for designing and implementing evaluation, validation and optimization of GenAI systems. You will define, design and develop LLMs as judges to evaluate task and system outputs across multiple applications, create datasets for benchmarking and evaluation and help design robust and scalable evaluation pipelines for both onine and offline GenAI systems.
:Responsibilities
Design, develop and apply state-of-the-art techniques for evaluating and validating AI agents and/or workflows.
Develop and implement LLM-as-a-Judge (or similar) for different tasks and roles for GenAI systems and tools.
Design and implement evaluation pipelines and benchmark datasets for evaluating model quality, relevance and system consistency for various applications.
Optimize and maintain judge LLMs to evaluate outputs for different use cases such as chatbots, RAG systems, cybersecurity experts and investigators.
Define evaluation KPIs and metrics for both models, systems and tools.
Validate and optimize datasets for various use cases.
Ensure the reliability, efficiency, and scalability of evaluation tools and pipelines for both online and offline use cases.
Work closely with AI/ML engineers to make evaluations a part of the production pipelines of GenAI applications.
Collaborate with cross-functional teams including product, research and data science.
Stay up to date with the latest developments in AI, machine learning, focusing on LLMs, exploring how emerging technologies can be applied to improve our evaluation and validation pipelines.