דרושים » דאטה » Big Data Engineer

Join us as a Data Engineer to help develop and maintain our rapidly growing data platform. You will be responsible for implementing scalable data pipelines, contributing to the development of custom tools, and ensuring massive datasets are processed efficiently to drive critical business decisions.
Responsibilities:
Implement and maintain scalable, production-grade data pipelines and infrastructure that support analytics and new product features.
Build and contribute to internal software and tooling that improves data team workflows, focusing on driving structure, maintainability, and engineering best practices.
Develop and manage key components of our new data platform, ensuring high reliability, performance, and scalability.
Work closely with security researchers, data analysts, and product teams to translate innovative cybersecurity ideas into functional, production-ready data solutions.
Apply and support best practices in data quality, governance, and observability to ensure our data systems remain robust and trustworthy as we scale.

Required Data Engineering Manager
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
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).

we are hiring a Software Engineer to help revolutionize the world of observability. Using cutting-edge AI-driven technology, we are redefining how organizations monitor, analyze, and optimize their systems-making observability more intelligent, efficient, and accessible than ever before. As we scale, we seek top talent to push the boundaries of innovation and shape the future of AI-powered observability. If youre passionate about solving complex challenges and building game-changing technology, join us in transforming how the world understands and interacts with data.

Responsibilities:

End-to-end development and ownership of products and features, from design to scalable and predictable production behavior
Solve diverse and complex problems in a high-scale, cloud-native environment
Collaborate with other engineers and product managers to improve product functionality, scalability, and performance
Design, develop, and maintain robust, secure, and efficient software solutions
Ensure high system reliability by implementing best practices in monitoring, observability, and automation
Review code, architecture, and data to identify and troubleshoot technical and performance issues
Work with AI/ML teams to integrate AI capabilities, including model monitoring, evaluation, and fine-tuning

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
** The role includes working on-site at our Jerusalem office several days per week.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

We are looking for a highly skilled and versatile Backend Engineer to join our development team. As a Backend Engineer, you will be responsible for designing, developing, and maintaining the backend infrastructure and components of our platform. As part of your role, you will also work on the frontend aspects of our platform and collaborate with stakeholders and cross-functional teams to optimize full-cycle system performance
Responsibilities:
Design, develop, and maintain backend systems and APIs to support our web applications
Implement and optimize data storage solutions, including databases, to ensure efficient and reliable data management
work closely with front-end developers to integrate backend functionalities and ensure a seamless user experience
Collaborate with product managers, stakeholders, and cross-functional teams to gather requirements, translate them into technical specifications, troubleshoot and resolve backend-related issues, and optimize system performance

We are looking for a highly skilled and versatile Senior Backend Engineer to join our development team. As a Senior Backend Engineer, you will be responsible for designing, developing, and maintaining the backend infrastructure and components of our platform. As part of your role, you will also work on the frontend aspects of our platform and collaborate with stakeholders and cross-functional teams to optimize full-cycle system performance.
Responsibilities:
Design, develop, and maintain backend systems and APIs to support our web applications.
Implement and optimize data storage solutions, including databases, to ensure efficient and reliable data management.
work closely with front-end developers to integrate backend functionalities and ensure a seamless user experience.
Collaborate with product managers, stakeholders, and cross-functional teams to gather requirements, translate them into technical specifications, troubleshoot and resolve backend-related issues, and optimize system performance.

We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions.
This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development.
The ideal candidate will work closely across teams within WorldQuant as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles.
They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

our company's ML Platform group builds and operates the core infrastructure that powers large-scale AI workloads across on-prem bare-metal GPU clusters and multi-cloud environments. Our goal is to deliver the modern infrastructure and tooling that accelerates our company's entire algorithm development lifecycle - from a researcher's first experiment to a production deployment.
We are a small, independent group of engineers with diverse skills across software, infrastructure, and systems. We set the standards, build the cross-company products, and take end-to-end ownership of everything we ship.
What will your job look like?
Design, develop, and maintain the Python framework that enables algorithm developers across our company to train, validate, quantize, and deploy deep learning models - locally, on-prem, and across cloud providers - through a single unified interface
Build high-performance data streaming libraries that feed large-scale distributed training pipelines in Rust with Python interfaces
Set the standard for reliable, reproducible research at scale - experiment tracking, configuration management, checkpoint handling, and multi-node training
Work directly alongside algorithm researchers to understand friction, propose solutions, and ship them - without layers of process in between
Contribute to open source when the right fix/feature belongs upstream.