דרושים » דאטה » Data Platform Engineer

Required Senior ML Data Engineer
Ramat Gan
Full time
The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

Required Data Engineer
The pioneer in AI-powered sports content technology, empowers more than 460 clients world-wide to connect with their fans through AI-tailored sports content experiences. Our platform automates the creation, management and distribution of content, enabling sports rights holders to expand reach, grow fan bases, and unlock revenue opportunities across digital platforms.
Why us:
Youll work in an awesome environment alongside some of the most innovative people in the industry, using cutting-edge technologies and tools (video editing, Gen AI, data, etc.). You have the opportunity to directly influence the products and tools used by our clients, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN - and thats just the beginning of what we have to offer! Join us and be a part of the best team in tech as we Fuel the Fandom worldwide.
What youll do:
Design and develop scalable, efficient services, APIs, and automations as founder of this area
Build data pipelines, ETL processes, and integrations that power products and internal tools
Own features end-to-end: design, implementation, CI/CD, monitoring, and observability
Develop and optimize data models, ensuring high-performance data infrastructure
Build and schedule workflows with python orchestrator and integrate with data platforms
Optimize performance, reliability, and security across services
Write high-quality, maintainable code in a rich data environment
Collaborate with Product, R&D, Operations, and Business to deliver impactful data-driven solutions
Work with SAAS environments and containerized deployments.

We are looking for a Data Engineer to join our Object Detection group and play a key role in managing and enabling data workflows that power our computer vision algorithms. Our team generates and processes large volumes of diverse data from multiple sources, and we need someone who can bridge the gap between raw data and algorithmic innovation. Working alongside algorithm developers and researchers, you'll be responsible for building robust data pipelines, ensuring data quality, and making complex datasets accessible and actionable for our detection models. This role requires both strong coding abilities and a deep understanding of data - you'll need to think like an engineer while understanding the unique needs of a research and development-focused algorithmic group.
What will your job look like:
Work on large-scale systems handling diverse data from multiple sources
Build and maintain robust data pipelines that enable algorithmic development
Evaluate various optional technologies and take part in decision-making
Own key features and services within the data infrastructure
Ensure data quality and accessibility for detection models and research needs
Work onsite in Jerusalem at least one day a week.

We are building a centralized intelligence system for the entire organization - a system that collects, consolidates, and analyzes all organizational data, and actively drives business workflows and decision-making.
This role exists to take that system to the next level.
As the Lead Organizational Intelligence Engineer, you will own the evolution of an internal platform that already influences how decisions are made across the company - and turn it into a foundational capability that fundamentally reshapes how the organization operates. Youll work end-to-end: from data ingestion and modeling, through analytics and AI-driven insights, all the way to decision workflows used by executives, R&D, product, and go-to-market teams.
You will operate as a senior individual contributor with broad organizational influence, while laying the technical and product foundations for a future team.
What Youll Do:
Own the architecture and implementation of a company-wide organizational intelligence system, end-to-end
Design and build data pipelines that ingest and unify data from across the organization and into our own platform
Define and evolve data models and semantic layers that create a shared, consistent language across teams and domains
Build advanced analytics and insight mechanisms that move beyond dashboards into decision-enabling workflows
Work directly with company executives to co-define requirements, identify blind spots, and translate strategic questions into systems and capabilities
Apply a product-driven mindset: deciding not just how to build, but increasingly what should be built and why
Leverage frontier AI tooling and agent-based workflows to accelerate development, improve system quality, and expand whats possible
Write and own production-grade code, setting a high bar for quality, reliability, and scalability
Influence technical and organizational workflows across the company to enable deeper intelligence and better decisions
Lay the groundwork for future externalization of these capabilities into customer-facing products