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We are looking for a sharp and driven Data Solutions Analyst to join a newly formed team and help build the analytical foundations behind some of our strategic growth initiatives from the ground up. This is a unique opportunity to influence how new businesses operate and scale across Amazon, D2C, Paid Media, and emerging growth channels. You will have ownership over both the measurement frameworks and the solutions that drive business growth.

Working at the intersection of Data, Marketing, Product, and Business, you will identify opportunities, define success metrics, uncover insights, and build the solutions needed to turn those insights into action. This role combines analytical ownership with hands-on solution development, leveraging data, automation, AI, and modern tooling to solve business challenges end-to-end. Success in this role is measured not only by the quality of your analysis, but by your ability to translate business challenges into scalable solutions that drive measurable impact.

Roles and Responsibilities:
Build analytical infrastructure, measurement frameworks, and decision-support capabilities from the ground up for new and rapidly growing business units.
Evaluate performance across Amazon, D2C, Paid Search, Paid Social, and emerging channels, identifying growth opportunities, business risks, and areas for optimization.
Translate business challenges into scalable solutions by combining AI powered automation, agents, workflows, and building tools that drive business impact.
Design, build, and maintain dashboards, monitoring systems, analytical products, and self-service tools that enable teams to make faster and better decisions.
Own the Semantic Layer: Maintain and scale our unified BigQuery Semantic Layer, ensuring a single source of truth for business and analytics metrics.
Partner closely with Marketing, Product, and Business stakeholders to understand business needs and drive end to end solutions from idea to implementation.

we are looking for a Senior Software Engineer.
You will be responsible for building the "brain" of main product, which is a distributed file system -the layer that manages orchestration, metadata, cluster membership, and implements complex logic required to manage hundreds of thousands of nodes, for cluster scaling, automated failover, zero-downtime rolling upgrades and "self-healing" to detect and remediate hardware failures or network partitions.
Design, implement, unit test, and maintain services that coordinate and the cluster
Optimize Performance: Work with complex data structures like spanning trees or LSM-Trees, concurrency control mechanisms (MVCC) to improve speed and efficiency.
Collaborate closely with cross-functional teams to translate backend capabilities into real-world impact

we are looking for a Senior Software Engineer.
The group is a high-powered team responsible for implementing algorithms at scales of 100s of PBs. The team also manages the core filesystem components, including blocks and metadata management, snapshots, RAID logic, object-store tiering, unique cloud disaster recovery features, and more. And most importantly, they skillfully handle the most delicate part of the solution - our customers data.
As a Senior Software Engineer, youll:
Design and develop distributed file system components to support data management features such as snapshots, replication, tiering, and advanced data reduction algorithms;
Participate in the design, architecture, and implementation of next-generation storage architecture;
Assist in technically managing initial storage implementations including proofs-of-concept;
Diagnose bottlenecks and implement clean and performant solutions to achieve unbeatable performance;
Design algorithms and data structures to make sure customer data is safe and coherent across our solution in a wide variety of failure modes; and
Constantly revisit the architecture, algorithms, and methodologies to improve productivity, reliability, and maintainability.

We are looking for a Technical Lead to drive the architectural direction and engineering excellence of this group. This is a senior, deeply hands-on role for a technology leader who can own the technical roadmap, mentor a team of elite engineers, and build the infrastructure that challenges platform to its theoretical limits.
What You'll Lead:
Define and own the technical architecture of the group's distributed testing and reliability platform - designing for massive scale, real-world workload simulation, and adversarial failure injection
Lead effort involving multiple engineers, setting technical standards, running architecture reviews, driving design decisions, and mentoring engineers to grow
Build the systems that orchestrate millions of concurrent IO operations, inject chaos at the infrastructure layer (latency, packet loss, hardware failures), and expose the hardest-to-find race conditions and consistency bugs
Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines
Drive observability and reliability engineering across the group - building telemetry pipelines that track P99 latency, jitter, and system health, turning quality into a quantitative discipline
Collaborate deeply with Core R&D, Storage Kernel, and Infrastructure teams - translating architectural knowledge into targeted reliability strategies
Establish engineering practices - design docs, production-grade code reviews, testing philosophy, and cross-team technical alignment

we are looking for a Software Engineer - Verification and Reliability.
In this role as a SDET (Software Development Engineer in Test), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures - latency, packet loss, and hardware crashes - to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.

We are looking for passionate individuals who want to make a real impact, working on state-of-the-art AI solutions that save lives and transform the driving experience. Join us in shaping the next generation of automotive technology.

Responsibilities
Develop real-time computational solutions for SoCs and hardware accelerators within edge devices.
Design, develop, and maintain Perception, Navigation and Planning stack software.
Port python algorithms to high quality, safe optimal C code.
Handle memory and runtime sensitive environment.

We are looking for an exceptional Deep Learning Engineer to join our core autonomy team. In this role, you will be responsible for building the AI-driven "brain" of our autonomous driving technology. Your focus will be on designing, training, and deploying state-of-the-art Deep Learning models that handle high-level prediction and driving policy. You will solve complex, real-world challenges by leveraging advanced neural network architectures to optimize decision-making under high uncertainty.

Responsibilities:
Model Training & Architecture: Design, train, and optimize cutting-edge Deep Learning models for prediction and driving policy.
End-to-End DL Development: Take ownership of the full DL lifecycle, from data curation and feature engineering to training, evaluation, and deployment.
Scalable Infrastructure: Develop robust pipelines for training and evaluating models on massive, real-world driving datasets.
Production Deployment: Optimize and integrate deep learning models to run efficiently in real-time within the core autonomy software stack.
Full-time availability at our Tel Aviv HQ.

We are looking for passionate individuals who want to make a real impact, working on state-of-the-art AI solutions that save lives and transform the driving experience. Join us in shaping the next generation of automotive technology.

Responsibilities
Manually tag objects in images with high accuracy and consistency.
Review and verify the accuracy of tagged data, making corrections as needed.
Work with predefined tagging guidelines and contribute to their improvement.
Collaborate with the machine learning team to understand tagging requirements and deliver datasets that meet project specifications.

Working on-site (office located in Tel Aviv).
Salary: 9,100 gross per month (50/hour, full-time), plus full social benefits, travel reimbursement, a 1,100 monthly meal card, and private health insurance after 3 months.

We are seeking a hands-on Applied AI Scientist to join our core R&D team and drive the development of next-generation AI systems for autonomous driving. This role sits at the intersection of applied research and deployment. This role sits at the intersection of applied research and deployment. You will work directly on our multi-layered autonomy architecture, with a primary focus on real-time predictive models for driving decisions. A deep technical role for someone who thrives on turning cutting-edge research into real, working systems under hard constraints.

Responsibilities:
Own the research-to-deployment cycle for driving models - from literature review and prototyping through to production integration.
Design, implement, and iterate on real-time predictive models, including vision-language-action (VLA) models.
Collaborate on reasoning systems, contributing to VLA models that handle planning across varied horizons.
Bridge cloud-scale training with edge deployment - work on model compression, quantization, speculative decoding, and efficient inference for embedded automotive platforms.
Evaluate and integrate state-of-the-art techniques from the broader AI research community into our autonomy stack.
Collaborate closely with internal R&D teams to unblock technical challenges, accelerate delivery, and raise the overall technical bar.

Our breakthrough World Model technology combines aerial imagery with real-time ground views to build an accurate, rich representation of the vehicle's environment. As part of our World Modeling team, you will drive the next generation of AI-powered, cloud-defined vehicle technology-tackling ambitious research and turning cutting-edge deep learning into real-world solutions.

Responsibilities
Research, design, and implement state-of-the-art deep learning models in computer vision (e.g., detection, segmentation, transformers, self-supervised learning).
Translate research into production-ready algorithms, writing clean, efficient, and scalable code in Pytorch.
Explore creative ideas, experiment with novel architectures, and continuously push beyond current SOTA.
Take ownership of your work end-to-end, from concept through prototyping to deployment in production.