לוח משרות דרושים הייטק דאטה בתל אביב יפו, לחיפוש זה נמצאו 100 משרות

Were on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the worlds first fully automated suite of vehicle inspection systems, with advanced AI at the core, spanning Machine Learning, GenAI, and computer vision across the automotive sector. With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, we stand at the forefront of automotive technological advancement. Our growing global team of over 300 employees is united around a culture of innovation, excellence, and teamwork as we build a safer automotive world.
We are looking for an experienced Research Scientist, Foundational Models to drive our long-term foundational model effort. You will design and train a single model that unifies all of our inspection segments (cars, trucks, fleets, tires, undercarriage, and future verticals) and serves as the basis for distillation into smaller, cheaper production models.
A day in the life and how youll make an impact
* Design and run large-scale pretraining experiments over our multi-segment inspection data.
* Develop self-supervised and multi-task learning recipes that transfer cleanly across vehicle segments and use cases.
* Build distillation pipelines that hand off compact, efficient models to production teams.
* Drive fast-adaptation methods so new segments and customers can be onboarded with minimal labels.
* Set and uphold ourresearch bar through rigorous evaluation, ablations, and publication-quality work.

We are seeking a skilled and motivated Data Engineer with expertise in Elasticsearch, cloud technologies, and Kafka. As a data engineer, you will be responsible for designing, building and maintaining scalable and efficient data pipelines that will support our organization's data processing needs.
The role will entail:
Design and develop data platforms based on Elasticsearch, Databricks, and Kafka
Build and maintain data pipelines that are efficient, reliable and scalable
Collaborate with cross-functional teams to identify data requirements and design solutions that meet those requirements
Write efficient and optimized code that can handle large volumes of data
Implement data quality checks to ensure accuracy and completeness of the data
Troubleshoot and resolve data pipeline issues in a timely manner.

Required Software & Data Engineer
Tel Aviv
We are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how we understand and improve our service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how we operate
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.

We are seeking a Senior Data Scientist / Applied Researcher to join our company's core product organization, where you will build and deploy next-generation AI models powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). The role centers on building and scaling intelligent systems powered by LLMs, advanced ML techniques, and agent-based architectures.
You will join a team within our companys Cyber R&D organization, leading the companys core product portfolio-while driving AI innovation and setting best practices across the domain. The group focuses on developing next-generation technologies, including training and optimizing LLMs and building advanced multi-agent workflows, while mentoring data scientists across R&D.
As a key technical leader, you will guide the evolution of our AI capabilities-converting cutting-edge ideas into impactful, production-ready systems and shaping our long-term direction.
We are looking for visionary data scientists and applied researchers eager to take on ambitious challenges and push the boundaries of AI in cybersecurity.
Responsibilities
Design and build advanced AI models and systems that power our companys core products and address real-world cybersecurity challenges.
Own initiatives end-to-end from identifying customer-driven problems and shaping solutions to experimentation, prototyping, and production deployment.
Drive forward new ideas and research directions, turning emerging concepts into practical, scalable solutions.
Influence the organizations roadmap and contribute to long-term technical strategy across our companys AI and product landscape.

we are looking for a Data Engineer.
What You'll Do:
Design, build, and maintain data pipelines and infrastructure
Develop and implement data quality checks and monitoring processes
Work with engineers to integrate data into our systems and applications
Collaborate with scientists and analysts to understand their data needs

Required Senior Data Analyst
Tel Aviv
As a Data Analyst you will be working with colleagues from various disciplines, such as - Product, Engineering, Marketing, Sales, Customer Success, Risk, Data Scientists within the team and other Data Analysts - on their KPIs, the way they observe information and the hardest questions each team is facing in order to drive insights and keep us a data driven company. You will play a key role in the ability of each team to keep scaling!
How your day is going to look, what you will be doing?
- Helping each team to take decisions based on data by:
Identify, analyze, and interpret trends or patterns in complex data sets to drive actionable insights
Define and implement KPIs across different teams
Accompany product features from tech design to feature performance
Translate product/business requirements to analytical logics, and create a very clear visualization which "tells the story" using a BI tool or other platform.

Required Senior Finops Analyst
Job responsibilities
What will you do?
The Senior FinOps Analyst will ensure financial requirements are clearly defined and translated into effective system solutions. This role focuses on gathering, structuring, and documenting detailed requirements for financial systems, driving alignment between Finance and Technology teams.
Key Responsibilities:
Requirement Gathering & Documentation: Work closely with Finance teams to understand their needs, pain points, and objectives. Translate business needs into structured, detailed, and well-documented requirements for Technology teams.
Financial Systems Enhancements: Partner with MIS and BI teams to ensure financial systems meet evolving business needs. Define system improvements and validate solutions before implementation.
Cross-Team Collaboration: Act as the primary link between Finance, MIS, BI, PMO, and other relevant teams, ensuring smooth communication and alignment of priorities.
Process Optimization: Identify inefficiencies in financial workflows and propose system-driven solutions that enhance automation and accuracy.
Strategic Initiatives Support: Contribute to large-scale financial system projects by providing clear, structured requirements and ensuring business objectives are met.

Lead the team building the agentic infrastructure powering Klaudia - our AI SRE. You'll own the architecture, set the technical direction, and push experimental ideas into production.

This isn't a coordination role. You'll be a technical leader who builds alongside your team - setting the bar for architecture quality, driving experimental bets, and turning research into production-grade systems.



What will you do?

Own the agentic infrastructure- You're responsible for the architecture of Klaudia's core - the systems that make autonomous investigation, root cause analysis, and self-healing possible at scale.

Build and grow your team- Hire great engineers, mentor them, run meaningful design reviews, and build a culture of high ownership and engineering excellence.

Drive experimental development- Run structured bets - LLM evaluation frameworks, new agent architectures, novel tool-use patterns - and bring the best ones to production.

Stay hands-on You'll design systems, review PRs critically, and write code where it matters. Your technical credibility is the foundation of your leadership.

Shape our AI strategy- Work closely with product and R&D leadership to define what Klaudia becomes next.



Why this role rocks?

Category-defining work- AI SRE is the hottest space in cloud infra. You'll be leading the team that defines what it means - not catching up to anyone.

Real autonomy- You'll set the technical roadmap for Core. No pre-solved problems handed down to you - you decide what gets built and how.

Build something that lasts- Hire and shape a team from an early stage. Your engineering culture decisions here will compound for years.

Serious engineering culture- High bar for craft, strong team around you, and leadership that respects technical depth over process theater.

we are looking for a Data science Team Lead.
As the Data Science Team Lead, you will lead a talented team of data scientists and ML engineers building the infrastructure, systems, and workflows for designing, training, evaluating, and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.
This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving, customer-specific model tuning, offline AI evaluations, and scalable ML systems in a production-grade SaaS environment.
If you are passionate about applied machine learning, fraud detection, and building intelligent systems at scale - we want you on our team.
What youl do:
Lead and mentor a team of Data Scientists and ML Engineers focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.

Were looking for a Senior Data & Analytics Architect to join our team and work directly with startup CTOs, engineering teams, and account teams. This is a hands-on, customer-facing architecture role where you will design and deliver production-grade data platforms on AWS.

The role is focused on turning real business problems into working systems, from early discovery and architecture design to supporting implementation. This is not a pure strategy or management role, its about making clear technical decisions and ensuring they hold up in production.

Work location: hybrid from Tel Aviv.

If you are interested in this opportunity, please submit your CV in English.

Key Responsibilities:
Design and deliver end-to-end data platforms on AWS, covering ingestion, storage, processing, and serving layers, including Well-Architected reviews and contribution to SOWs and HLDs.
Work directly with startup customers to understand requirements, challenge assumptions, and shape practical solutions.
Lead technical discussions, workshops, architecture reviews, and POCs.
Translate ideas and early concepts into clear architectures, including HLDs, SOWs, and implementation direction.
Make and explain trade-offs across cost, performance, scalability, and complexity.
Stay close to delivery, supporting teams to ensure solutions are implemented correctly.
Collaborate with Data Engineers, DevOps, Solution Architects and Account Managers to move projects from concept to production.
Contribute to internal standards, reusable patterns, and reference architectures.
Operate in a fast-paced, project-based environment with multiple customer engagements.
Stay up to date with modern Data Engineering and Analytics practices, and contribute to internal enablement, patterns, and knowledge sharing.
Work in a customer-facing environment that includes occasional travel, both locally for meetings and events, and internationally around once per quarter.

Were looking for a seasoned R&D Team Leader to join our top-notch technology R&D team, reporting directly to the VP R&D. In this role, you will drive technological innovation, oversee the development of cutting-edge features, and guide the team in delivering scalable, high-quality products. You will combine hands-on technical leadership with strategic oversight, ensuring that our platform continues to evolve and deliver impactful solutions for our clients. As part of an AI-first company, our web team is deeply involved in creating and integrating AI-driven features to enhance our digital offerings.



Key Responsibilities:

Lead the R&D team in developing new features and enhancing our platform.
Oversee the end-to-end development lifecycle, from ideation to deployment.
Ensure high-quality code, scalable architecture, and smooth product delivery by implementing best practices in software development.
Mentor and support team members in their professional growth.
Troubleshoot and resolve complex technical challenges in collaboration with the team.
Collaborate with cross-functional teams including Product, Data, and AI to align development efforts with company goals.
Drive innovation and stay updated on new technologies to keep us at the forefront of the industry.

we are growing fast, and as we grow we scale both in the number of patients we treat and in the number of products we have in our portfolio. Your mission is to design and build the next-generation data infrastructure and pipelines, in addition contributing to an ongoing project that serves both our customers and internal data teams with scalable and reliable solutions.

You will:
Make a critical contribution to shaping and developing the core of our Data Platform used for AI research and business intelligence, from design to implementation.

Design and build complex data pipelines to move and manipulate data from a wide variety of data sources.

Create a system that will be used to support our data product offering.

Closely collaborate with various teams, including Software Engineering, AI Engineering and Product Management .
Tech stack:

We are running on AWS with Python as the main programming language for the backend. We are using various technologies such as S3, DBT, ETL, ELT, Spark, DynamoDB, Postgres, RabbitMQ, Docker, Redis, Prometheus, Terraform and others. We are always open to new technologies and tools that will help us to do our job even better.

What success looks like:
Self-contributor who excels at working independently and can also collaborate effectively as a valuable team member.

Mentor and advise other team members in code review, performance, scalability and more.

Eager to learn new things and also proactively suggest new ideas and initiatives.

Excellent communication and collaboration skills.

Team player, highly motivated, can-do approach.

We are looking for an experienced and passionate Data Engineer to join the Data Engineering Team in our rapidly growing TLV R&D site!
You will be instrumental in maintaining current pipelines and expanding our data semantic layer to support both traditional analytics and our future AI/ML initiatives.
Responsibilities include working alongside developers from the BI and Backend teams, architects and business decision makers in order to implement data pipelines and improve data architecture and infrastructure.
The Data Engineering Team focuses on building long term, scalable self-service solutions for the organizational growing data needs.
What You'll Do:
Design & Build Robust Pipelines: Develop, deploy, and maintain scalable, highly reliable, and idempotent ELT data pipelines using Python and orchestration tools like Airflow.
Own the Data Model: Lead data transformation and modeling efforts within our cloud data warehouse (e.g., Snowflake, AWS) using dbt, ensuring adherence to modern analytics engineering best practices (modularity, DRY principles, and clear separation of staging and data marts).
Expand the Semantic Layer: Architect and grow our centralized semantic layer to establish a "single source of truth" for business metrics, powering both traditional BI dashboards and upcoming AI initiatives.
Champion Data Quality & Reliability: Implement rigorous data validation, testing, and monitoring to ensure data integrity and build trust with downstream consumers.
Enable Self-Service Analytics: Design intuitive, long-term data infrastructure solutions that empower business stakeholders, analysts, and developers to easily and independently query organizational data.
Cross-Functional Collaboration: Partner closely with Backend developers, BI analysts, architects, and business decision-makers to translate complex business requirements into efficient technical architectures.

We are looking for a Senior Analytics Engineer to help design and build the engineering foundation that powers analytics across the organization.
Our goal is to create a modern data environment where analytics development is fast, reliable, scalable, and increasingly automated. This includes building strong data warehouse foundations, scalable modeling layers, and introducing AI-powered tools and automation that accelerate how data products are built and used.
In this role, you will be part of an analytics squad, working closely with analysts and business stakeholders while building the infrastructure, automation frameworks, and intelligent tooling that enable analytics to scale across the organization.
This is a unique opportunity to help build the next generation of the data organization.
Key Responsibilities:
Lead AI adoption in the analytics platform, building tools and workflows that automate analytics development, dashboards, and data exploration
Design and build scalable data warehouse models and transformation layers
Build and optimize ETL pipelines and core analytics infrastructure (Bronze / Silver)
Improve performance, reliability, and scalability of the analytics platform
Develop automation and internal tools that accelerate analytics workflows
Enable self-serve data access across the company through semantic layers and reusable datasets
Collaborate with analysts and business teams within an analytics squad

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a talented Data Engineer to help build and enhance the data platform that supports analytics, operations, and data-driven decision-making across the organization. You will work hands-on to develop scalable data pipelines, improve data models, ensure data quality, and contribute to the continuous evolution of our modern data ecosystem.

Youll collaborate closely with Senior Engineers, Analysts, Data Scientists, and stakeholders across the business to deliver reliable, well-structured, and well-governed data solutions.


What Youll Do
Engineering & Delivery
Build, maintain, and optimize data pipelines for batch and streaming workloads.

Develop reliable data models and transformations to support analytics, reporting, and operational use cases.

Integrate new data sources, APIs, and event streams into the platform.

Implement data quality checks, testing, documentation, and monitoring.

Write clean, performant SQL and Python code.

Contribute to improving performance, scalability, and cost-efficiency across the data platform.

Collaboration & Teamwork

Work closely with senior engineers to implement architectural patterns and best practices.

Collaborate with analysts and data scientists to translate requirements into technical solutions.

Participate in code reviews, design discussions, and continuous improvement initiatives.

Help maintain clear documentation of data flows, models, and processes.

Platform & Process

Support the adoption and roll-out of new data tools, standards, and workflows.

Contribute to DataOps processes such as CI/CD, testing, and automation.

Assist in monitoring pipeline health and resolving data-related issues.