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 data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives 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 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

We are seeking for a talented Data Science Team Lead to join our development center in Israel, a fast-paced and innovative environment. You are a passionate data professional with proven experience in building and growing high-quality data teams, which will play a pivotal role in driving the execution and delivery of advanced Machine Learning models and algorithms, through mentorship and hands-on development, and by working closely with clients to understand their needs and key objectives.
Responsibilities :
Serve as a team expert in the most advanced Machine Learning methodologies, helping to plan and implement successful and impactful data science projects
Manage experienced team of data scientists, providing career guidance and performance evaluation to develop and retain talent
Solve non-routine analysis problems based on high-dimensional, complex data sets, by actively mentoring and coding
Lead deployment of large-scale data pipelines, ensuring a seamless delivery
working directly with key client executive decision makers and acting as the leading expert for best-practice data-driven solutions
Establish strong cross-functional relationships throughout the organization to improve our customer experience and set of offered skills.

Were seeking an experienced and skilled Data and AI Infra Tech Lead to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data and AI infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure.
As a tech lead, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team.
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.

This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a ML & Big Data Analyst look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of data and algorithms.
Utilize your deep understanding of data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.

Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.
Why is this role so important?
As the most trusted platform for measuring online behavior, millions of people rely on insights daily as the ground truth for their knowledge of the digital world. Producing these insights requires large scale raw data to be ingested reliably in high scale to provide stable signals for analysis. As a Data Engineer you will have the opportunity to perform hands-on work and own raw data ingestion pipeline end-to-end. Your work will have a direct impact on the quality and reliability of our data and the insights that our products are delivering to our customers.

Were seeking a visionary and technically hands-on AI Team Leader to join and take charge of driving innovation across our core AI systems.
As the AI Team Leader, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform.
You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.
This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.
Key Responsibilities:
Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiatives-identify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.

Were looking for an experienced Engineering Group Manager to join our growing R&D organization in Tel Aviv. In this role, youll lead and scale a group of teams responsible for the heart of AI platform, including our AI team, Chat AI product team, and Incubation team. A major focus of this role is to lead and grow the Data Science team, including machine learning research, ML model development, and MLOps practices to ensure production-ready, scalable, and reliable AI solutions.

You will play a key role in shaping and executing our technical vision, driving the evolution of our conversational AI and voice solutions, and building a strong, high-performing engineering organization. This role reports to the CPTO.

Responsibilities
Lead, scale, and mentor an engineering group of 15-20 engineers, delivering complex, AI-driven products at scale.
Manage two Team Leads and provide direct leadership to specialized teams, including the AI team and Data Science team, working closely with a dedicated AI Architect.
Partner closely with the CTO to translate technical vision into execution and ensure strong alignment across teams.
Collaborate deeply with Product Managers to define and execute the roadmap for core AI engine and chat experiences.
Oversee the development and deployment of machine learning models, including model design, evaluation, optimization, and production integration.
Drive continuous improvement of R&D processes, structure, and engineering culture to support rapid growth and high-throughput environments.
Foster technical excellence, mentor future leaders, and build a strong leadership pipeline within .
Own cross-functional collaboration, ensuring strong synchronization between your group and other departments across the company.

Were looking for a hands-on Engineering Team Lead to join our AI Group.
This role combines people leadership, senior-level backend development, and infrastructure-oriented thinking, and plays a key part in building and scaling AI-powered capabilities across Bobs product.
As a Team Lead in the AI group, you will lead a team of backend engineers while remaining actively involved in designing and implementing robust, scalable systems that support AI features used by thousands of customers.
If youre passionate about leading people, shaping technical direction, and staying hands-on in complex backend and infrastructure challenges - this role is for you.
Why Join the AI Group?
Lead a team at the core of Bobs AI strategy and execution.
Influence both product-facing AI features and the underlying technical foundations.
Work in a highly collaborative environment with strong Product, Infra, and Data partners.
Make a real impact at scale while growing as a technical and people leader.
Job responsibilities
What Youll Do
Technical Leadership & Hands-on Development
Lead the design, development, and operation of backend services and infrastructure that power AI-driven features.
Take ownership of end-to-end delivery - from discovery and architecture through implementation, testing, deployment, and monitoring.
Address scalability, performance, and reliability challenges in production systems handling real-time AI interactions.
Work closely with Infrastructure, Data, DevOps, Product, and Design teams to ensure seamless integration of AI solutions into the broader platform.
Drive high engineering standards through code reviews, architecture discussions, testing practices, and automation.
Team Leadership & Growth
Lead, mentor, and grow a team of backend engineers within the AI group.
Own hiring, onboarding, coaching, and professional development of team members.
Foster a culture of ownership, collaboration, learning, and technical excellence.
Support engineers in growing their scope and taking end-to-end responsibility.
AI Platform & Developer Experience
Contribute to and evolve shared AI infrastructure, internal services, SDKs, and tooling.
Improve developer experience by enhancing observability, CI/CD flows, configuration, and internal frameworks.
Collaborate with Architects and DevOps to align AI infrastructure with long-term platform strategy.

We are looking for a talented and dedicated Data Analyst - ML & Big Data who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a Data Analyst - ML & Big Data look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of data and algorithms.
Utilize your deep understanding of data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.