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Required Senior Data Engineer I - GenAI Foundation Models
21679
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

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.

we are looking for a Senior Software Engineer.
As a Senior Engineer on the Guardrails team, youll take ownership of our most high-leverage features: the Policy Engine and approval workflows. These aren't just features; they are the logic layer that governs how risk is accepted or blocked across the entire platform. You will build sophisticated, cross-platform systems that turn messy compliance requirements into streamlined, automated workflows, directly shaping how modern teams ship secure software.
You will join a team that is:
Redesigning Core Architecture: You will help lead the migration of our policy logic into a high-scale, event-driven data pipeline. You will move us away from legacy services toward a modern, centralized architecture capable of enriching millions of security findings in real-time.
Solving Complex Identity Challenges: You will tackle one of our hardest engineering problems: persistence and consistency. You will design systems that track software components across different branches and repositories, ensuring that risk decisions follow the code wherever it goes.
Operating at the Intersection of the Platform: This is a highly collaborative role. You will work across the stack, partner with the scanning engines, data platform, and developer tooling (CLI/IDE) teams, to ensure governance logic is unified and seamless across the entire development lifecycle.

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.

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.

We are seeking an experienced and driven Senior Support Engineer to join our Global Customer Support team. In this role, you will be responsible for investigating, diagnosing, and resolving complex customer issues with the Real-time Data Platform. Youll work closely with engineering, technical writers, and client services to deliver exceptional support and help customers achieve success with at scale.
What Youll Do:
Troubleshoot and resolve technical issues for customers across diverse environments (cloud, hybrid, on-prem).
Collaborate cross-functionally with Engineering to drive resolution of complex problems and contribute to product improvement.
Participate in real-time customer remediation efforts and live incident resolution.
Act as a customer advocate to ensure timely and accurate issue resolution.
Support enterprise customers with mission-critical systems and real-time data use cases.
Assist with new deployments, configuration guidance, and performance tuning.
Write and maintain high-quality documentation and Knowledge Base articles to scale support capabilities.
Contribute to a collaborative, agile, and globally distributed support team.

Required PhD Machine Learning Research Intern
27984
Role Description
About the team: The internship is open for PhD students in a machine learning related field like Planning with LLMs, Multilingual Training Adaptation, Recommender System and Ranking, Bidding, Synthetic Data Generation, Entity Representation Learning, Reinforcement learning and Classification.
Applicants are asked to attach with their CV the email address of their supervisor or co-supervisor. This email will be used to ask for a recommendation letter at a later date.
Please complete your application before March 31st, 2026. Participation in the internship program requires that you are located in Israel for the duration of the internship program (3 months)
Role Description:
As a Machine Learning Research intern at Booking.com in Tel-Aviv, you will have the opportunity to tackle real world problems by pushing the boundaries of the state-of-the-art, with the goal of publishing your work.
You will join us for a 3-month internship (preferred start date: May) focused on Data-Centric AI. In this project, you will tackle the "glass ceiling" of NLU performance: inherent ambiguity in annotation guidelines and label taxonomies. You will move beyond traditional noise reduction to investigate why human annotators disagree and how these disagreements corrupt "ground truth," directly influencing how we evaluate and improve state-of-the-art models.
Key Job Responsibilities and Duties:
Survey the Landscape: Conduct a comprehensive literature review to synthesize current approaches to data ambiguity, identifying the strengths and limitations of existing methods in handling label noise and taxonomy gaps.
Innovate & Design: Devise novel techniques and metrics to detect, quantify, and resolve inherent ambiguities within NLP datasets and annotation guidelines.
Experiment & Validate: Design and execute rigorous experiments to evaluate your proposed methods, measuring their impact on model reliability and ground truth accuracy.
Publish Findings: Summarize your conclusions and contribute to writing a research paper with the aim of submitting to a top-tier NLP conference (e.g., ACL, EMNLP).

we are looking for a technically sharp, customer-focused Solutions Architect to help drive adoption of our blazing-fast real-time data platform. In this high-impact role, youll partner closely with our sales team to win business by translating complex technical capabilities into clear, compelling value for our customers.
Based in Israel, youll serve as the technical expert and strategic advisor throughout the sales process - from discovery to demo to deployment. Whether its architecting a high-scale solution, answering in-depth questions, or running a proof of concept, your expertise will be key to helping customers realize the power .
This is a pre-sales position.
Responsibilities:
Preparing and developing technical presentations to explain our company's products or services to customers.
Discussing equipment needs and system requirements with customers and engineers.
Collaborating with sales teams to understand customer requirements and provide sales support.
Researching, developing, and identifying modifying products to meet customers' technical requirements and needs.
Soliciting and logging client feedback and evaluating the data to create new sales and marketing strategies to target customers.
Identifying areas for improvement and communicating these issues as well as possible solutions to upper management, including product managers.
Setting and achieving sales goals and quotas.
Training other members of the sales team on the technical aspects of the company's products and services.

Required Machine Learning Scientist II - GenAI Evaluation
20717
Role Description:
As a Machine Learning Scientist, your work will focus on the evaluation and optimization of generative AI systems. You will develop and fine-tune Judge LLMs to assess model outputs across a variety of tasks, design robust evaluation frameworks for agentic workflows, and build scalable pipelines for synthetic data generation. The team also plays a critical role in multilingual evaluation, enabling GenAI applications to support market expansion across all supported languages.
Key Job Responsibilities and Duties:
Develop and apply state-of-the-art techniques for evaluating generative AI systems, with a focus on agent workflows, multilingual output, and task-specific Judge LLMs.
Design and implement scalable evaluation pipelines, including synthetic data generation and benchmarking for model quality, relevance, and consistency..
Optimize and maintain Judge LLMs to assess outputs across dialog systems, Q&A, and trip planning use cases.
Conduct in-depth data analysis to define and track evaluation metrics, validate label quality, and explore performance across different languages and user scenarios.
Ensure the reliability, efficiency, and scalability of evaluation tools and frameworks in both offline and online environments.
Collaborate closely with ML engineers to integrate evaluation components into production pipelines, supporting continuous improvement of GenAI applications.
Work cross-functionally with product, research, and analytics teams to align evaluation strategies with business goals and user impact.

We are looking for an experienced Machine Learning Engineer to build and scale production-grade ML solutions, primarily on large-scale tabular automotive data for quality and cybersecurity products. Youll help define the engineering standards that enable the Data Science team to deliver at scale, with opportunities to own selected ML features end-to-end.
Youll work with massive (often live-streaming) automotive datasets and real-world constraints around latency, CPU, memory, and I/O. This is a highly collaborative role, and youll partner closely with data science and data engineering teams. Youll be driving technical alignment through clear communication and mentoring others via design and code reviews.
This role is full-time and based in Herzliya, Israel.
Responsibilities
Act as the DS engineering axis: drive designs with focus on performance (I/O, CPU, memory, latency, cost).
Lead heavy ML engineering efforts when needed (optimization, scaling, reliability), while collaborating with other team members and supporting them in their ML-related projects.
Own selected ML features and projects end-to-end, including DS work (EDA, features, modeling, evaluation) plus production delivery, monitoring and iteration.
Build production tabular - ML components: training, batch/near-real-time scoring, inference services, and shared libraries.
Set standards and tooling for profiling and preventing performance regressions.
Partner with the data engineers on data / ML contracts (schemas, SLAs, formats/partitioning) between pipelines and ML components.
Raise the bar via mentoring, documentation, and a strong code/design review culture, in the Data Science team.

We are looking for a Quant Algorithms Developer to join our research team and play a pivotal role in contributing to the company's ongoing success
What you will do:
End-to-end development and deployment of high-frequency trading algorithms consisting of:
Creative thinking, performing research and literature review
Conceiving innovative and novel ideas in the fields of machine learning, statistics, and signal processing
Development and application of trading algos in a highly competitive real-time environment
Collaboration with other researchers/developers

Required Senior Data Engineer
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. Our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data scientists, data architects, and data analysts, to provide solutions using a use case-based approach that drives the construction of technical data flows.

We are looking for an algorithm researcher to join our team and play a pivotal role in contributing to the company's on-going success.
What you will do:
End to end research, development and deployment of high frequency trading algorithms consisting of:
Creative thinking, performing research and literature review
Explore and design innovative and novel ideas in the fields of machine learning, statistics and signal processing
Development and application of trading algos in a highly competitive real time environment
Enjoy a very short development cycle from concept to live trading
Collaboration with other researchers / developers

We are looking for a talented Business Development Representative (BDR) to join our team and help drive pipeline growth across our core solutions.
You will operate in the B2B/B2E automotive and smart mobility market, one of the fastest-growing segments in enterprise technology. The role involves prospecting into leading global automakers, tier-1 suppliers, IoT platform providers, and smart mobility companies. You will engage in complex enterprise sales cycles and work directly with senior stakeholders across cybersecurity, IT, quality, and AI organizations. You will also play a hands-on role in refining the outbound playbooks and processes that support scalable growth.
This role is full-time and is based in Herzliya, Israel.
The role follows a Monday-Friday work week with a hybrid schedule, three days in the office and two days remote. Flexibility to work North America (East Coast) hours is expected to support global prospects and customers as needed.
Responsibilities
Conduct outbound prospecting via multi touch point sequencing, including email, phone, LinkedIn, and other channels to generate qualified meetings for Sales executives
Engage and qualify inbound leads from marketing campaigns, ensuring timely follow-up and conversion into opportunities
Research and identify target accounts, key decision makers, and deep industry trends, spanning automotive OEMs, IoT, smart mobility companies, and tier-1 suppliers
Partner closely with Marketing, Sales executives, partners and alliances team, as well as Product and Customer Success teams to refine outreach strategies and improve conversion rates
Boost visibility and maintain accurate, up-to-date prospect interactions in Salesforce
Test and optimize messaging, outreach cadences, and engagement strategies based on performance data
Provide feedback on lead quality and collaborate with Marketing on campaign alignment
Be GenAI-savvy and willing to test and expand, in a controlled and responsible way, what can be achieved with AI tools.

Were looking for an exceptional, driven, and technically visionary Staff Engineer to help shape the future of our platform and accelerate our mission to simplify taxes for everyone.
Youll play a central role in designing and building scalable systems and tools that enable our teams to deliver exceptional user experiences with speed and confidence.
If you're passionate about technical leadership, enjoy solving complex architectural challenges, and want to make a meaningful impact on millions of users, wed love to have you join us.
Responsibilities:
Critical, cross-functional engineering initiatives from design to development and deployment, ensuring quality and scalability.
Participate in technical decision-making and knowledge sharing across multiple teams.
Collaborate with Product, UX, and other stakeholders to deliver seamless and data-driven experiences.
Evaluate and introduce new tools, technologies, and practices that raise the bar for engineering excellence.
Guide by example - service ownership, observability, and operational best practices across the engineering organization.
Promote a culture of high standards, clean code, testing, and continuous improvement.