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abra SAP Department is seeking for a Technology Integration Coordinator (SAP Projects) We are looking for a skilled Technology Integration Coordinator to join large-scale SAP transformation projects and serve as a key coordination point between project teams, technical teams, business stakeholders, and external vendors. This role combines project coordination responsibilities with technical involvement. The ideal candidate is not only able to track and drive tasks, but also has the technical understanding required to participate in discussions, coordinate activities across multiple teams, facilitate communication between stakeholders, and support integration-related processes. The position offers the opportunity to work on strategic SAP initiatives involving cloud and on-premise environments, while collaborating with infrastructure, cybersecurity, networking, development, and SAP implementation teams. A full-time position, based in Central Israel.
?Key Responsibilities:
* Coordinate and drive activities across project, infrastructure, cybersecurity, networking, development, and vendor teams.
* Monitor project tasks, dependencies, risks, and deliverables to ensure successful execution.
* Facilitate communication and alignment between business and technical stakeholders.
* Support integration activities across SAP, cloud, and on-premise environments.
* Participate in technical discussions and help translate requirements into actionable tasks.
* Manage and track activities using Jira and Agile methodologies.
* Represent the organization in day-to-day coordination with external implementation partners and vendors.

We are looking for someone who operates independently and leads projects, not someone who waits to be handed a task. You will own initiatives from idea through production, collaborate with product, design, and hardware teams on Bluetooth/BLE and IoT integrations, and mentor other engineers along the way.
This role is fully onsite.

Responsibilities
As a Senior Software Applications Engineer, you will shape the architecture and quality of our mobile applications and the Python services that power them. You will work end to end, from native iOS interfaces down to the hardware our products communicate with, setting technical direction and the standards other engineers build upon.

We are looking for a highly skilled Senior Environmental System Test Engineer - Camera & Laser to join our team in Herzliya.

Responsibilities
Lead end-to-end environmental testing and characterization of camera and laser sensor systems, encompassing optical performance, mechanical alignment, and environmental robustness.
Define and execute environmental test protocols addressing real-world conditions, including: Solar/sun influence - direct and indirect illumination interference on sensor performance; Rain and moisture - water ingress, droplet effects on optical paths, condensation; Motion and walking scenarios - dynamic movement, vibration, and stabilization assessment.
Perform system-level validation ensuring sensor subsystems meet performance specifications across all environmental boundaries.
Design and build repeatable, controlled test environments and fixtures for rigorous physics-based evaluation.
Collaborate with cross-functional teams (optics, firmware, mechanical, and research) to translate environmental requirements into actionable test plans.
Analyze and report test data, providing clear recommendations for design improvements.

Analyze and investigate RF signals across the electromagnetic spectrum.
Identify and diagnose spectrum anomalies and mitigate electromagnetic interference (EMI).
Operate measurement equipment such as Spectrum Analyzer, Network Analyzer, and Signal Generator.
Collaborate with technical teams to implement RF solutions.
Job location- Central Israel
scope of hours: 100-160 hours.

We are looking for a highly skilled Senior Sensor & Embedded System Testing Engineer to join our team in Herzliya.
In this role, you will help create the full data lifecycle that underpins our models: from designing what data we collect, through curation and quality monitoring, to running rigorous experiments that drive model improvements. You will work closely with other ML and Data Engineering teams to ensure our models are trained on the best possible data, reaching the best accuracy, and that we deeply understand when and why they don't perform as expected.

The selected candidate will assume responsibility for the configuration of advanced camera and laser sensor systems, and for the rigorous validation of their functionality at the embedded level. This role encompasses interface verification, timing analysis, performance characterization, firmware integration support, and direct collaboration with research and physics evaluation programs.

Responsibilities
Lead the configuration and bring-up of camera and laser sensor subsystems within embedded platforms.
Define, develop, and execute comprehensive system-level validation and definition testing strategies.
Characterize sensor performance across optical, electrical, and timing domains.
Validate sensor interfaces (MIPI CSI-2, SPI, I²C, LVDS) and ensure compliance with system specifications.
Support firmware integration activities, ensuring robust sensor operation within the full system stack.
Design and maintain automated test infrastructure for sensor validation and regression testing.
Collaborate closely with physics, optics, and research teams to support experimental evaluation campaigns.
Perform root-cause analysis of issues spanning hardware, firmware, optics, and sensor subsystems.

We are looking for a talented and curious Audio Machine Learning Engineer to join our growing Machine Learning team in Herzliya. In this role, you will help create the full data lifecycle that underpins our models: from designing what data we collect, through curation and quality monitoring, to running rigorous experiments that drive model improvements. You will work closely with other ML and Data Engineering teams to ensure our models are trained on the best possible data, reaching the best accuracy, and that we deeply understand when and why they don't perform as expected.

Redefine the future of human-computer interaction and the way people communicate. Contribute to products that shape mobile computing and create breakthrough technologies in the audio domain.
In this role, you will push the boundaries of audio solutions across the full stack - from data pipelines and model training to optimization for our silicon. You'll collaborate with world-class researchers and engineers to ship technology that reaches hundreds of millions of users, while upholding our unwavering commitment to privacy.

Responsibilities
Work with unique, proprietary datasets - developing algorithms to process them and devising metrics to evaluate and improve quality.
Design and implement machine learning models focused on the audio domain, for low-latency feedback and high-fidelity streaming.
Drive data quality insights and influence the design of our end-to-end system.
Conduct both cutting-edge research and product-oriented development.
Collaborate closely with researchers, engineers, and product teams to bring new capabilities to life.

Play a part in shaping the future of human-computer interaction. Contribute to products that are redefining mobile computing and creating breakthrough technologies in conversational AI, speech recognition, and natural language understanding and generation.

We are seeking a passionate and experienced Machine Learning Engineer to join our team. In this role, you will push the boundaries of on-device speech recognition and NLP, working across the full stack - from data pipelines and model training to optimization for our silicon. You'll collaborate with world-class researchers and engineers to ship technology that reaches hundreds of millions of users, while upholding our unwavering commitment to privacy.

Responsibilities
Work with unique, proprietary datasets - developing algorithms to process them and devising metrics to evaluate and improve quality.
Design and implement machine learning models spanning speech recognition and NLP domains.
Drive data quality insights and influence the design of our end-to-end system.
Conduct both cutting-edge research and product-oriented development.
Collaborate closely with researchers, engineers, and product teams to bring new capabilities to life.

Join our team as a Machine Learning Engineer and help shape the future of on-device AI. You'll research, design, and deploy cutting-edge deep learning models optimized for our silicon edge devices, working across the full ML lifecycle alongside hardware, software, and product teams.

We are looking for a talented and motivated Machine Learning Engineer to join our team. You will work within a collaborative, research-driven engineering culture that values innovation and rigor, with the opportunity to build impactful AI products deployed at scale on real devices. We offer competitive compensation, benefits, and opportunities for professional growth.

Responsibilities
Research and design state-of-the-art deep learning models optimized for resource-constrained our silicon edge devices.
Drive projects across the full ML lifecycle, from ideation and experimentation to production deployment.
Collaborate closely with cross-functional teams including hardware, software, and product.
Continuously evaluate and adopt new techniques to improve model performance and efficiency on-device.

Play a part in shaping the future of human communication technology. Contribute to a unique multidisciplinary system that models and understands human interaction, redefining what's possible with computer vision, physics, and signal processing at the edge.

In this role, you'll be at the forefront of a one-of-a-kind technical challenge, developing and implementing novel methods for processing and enhancing a proprietary sensor that models human communication. You'll work hands-on with exclusive data: designing the algorithms that process it, and defining the metrics that evaluate and drive its continuous improvement.

Your insights will carry real weight, directly informing sensor decisions and shaping the architecture of the broader system. You'll lead multi-level research efforts to advance a truly unique sensor, drawing on a rich and diverse technical toolkit spanning signal processing, computer vision, physics, and state-of-the-art deep learning. You'll own proprietary data collections using high-end computer vision techniques, studying signals from their raw-level behavior all the way through to their top-level impact on product performance.

This is a role that lives at the intersection of deep research and real-world impact. You'll conduct cutting-edge investigations and translate your findings directly into product outcomes, influencing decisions across the full stack, from hardware choices and algorithmic pipelines to the features that reach the final product.

Responsibilities
Develop and implement novel algorithms for modeling and understanding human communication, combining 2D/3D computer vision, signal processing, and deep learning.
Work with unique proprietary datasets - design large-scale data processing pipelines, define quality metrics, and provide actionable feedback to improve data collection and labeling workflows.
Devise and implement rigorous evaluation frameworks to measure model and data quality, and drive continuous improvement across the system.
Design neural network architectures optimized for SOTA accuracy and computational efficiency.
Stay current with the latest research across computer vision, signal processing, and efficient ML; evaluate and integrate relevant advances into the team's work.
Contribute to internal tooling and best practices for reproducible, scalable ML research and deployment.

We are looking for an ML Engineer to join a research-oriented group developing physics-informed neural networks for advanced sensing and optical measurement systems. The role focuses on training, validating, and improving neural network models that combine data-driven learning with physical modeling, simulation, and experimental measurements.

Responsibilities
Develop, train, and evaluate neural network models for physics-based sensing and reconstruction tasks.
Incorporate physical knowledge into ML models through data generation, model architecture, loss functions, constraints, or regularization.
Work with simulated and experimental datasets, including data. preprocessing, augmentation, validation, and error analysis.
Build robust training pipelines using Python and modern ML frameworks such as PyTorch.
Compare model predictions against ground-truth data from simulations, optical experiments, or measurement systems.
Collaborate with physicists and optical engineers to understand underlying physical models and translate them into ML workflows.
Analyze model performance, identify failure modes, and improve generalization from simulation to real-world data.
Design experiments to evaluate model robustness, sensitivity, uncertainty, and accuracy.