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Play a part in shaping the future of human-computer interaction. As an MLOps Engineer, you will be the backbone of the machine learning infrastructure that powers our speech, audio, and conversational AI teams - ensuring their models are trained on the best possible data.
You will bridge the gap between research, data science, and engineering, owning the full ML lifecycle from large-scale data pipelines and distributed GPU training through to low-latency, high-fidelity inference and optimization. You'll partner closely with Audio ML Engineers, Speech ML Engineers, and ML Data Scientists to remove friction across their workflows and accelerate the path from research to product.

The MLOps Engineer will drive end-to-end quality and operational excellence across data ingestion, model training, deployment pipelines, and MLOps tooling for our speech and audio ML platforms. This hire will build, deploy, and optimize production-grade systems with a strong emphasis on scalable, GPU-accelerated infrastructure. You will own the training infrastructure that powers distributed and self-supervised model training on HPC and Slurm-managed clusters, as well as the inference pipelines that bring low-latency, high-fidelity audio and speech models to production. You will establish standard methodologies for model integration, deployment, monitoring, and reproducibility using CI/CD principles.

Responsibilities
Design, build, and operate large-scale data pipelines for proprietary audio and speech datasets - supporting curation, quality monitoring, and validation at scale alongside our ML Data Science team.
Partner closely with Audio ML Engineers, Speech ML Engineers, ML Data Scientists, and product teams to define metrics, gather requirements, and bring new capabilities to life.
Build and operate distributed GPU training workflows, including job scheduling and resource management on Slurm-managed HPC clusters, for both supervised and self-supervised methods.
Optimize model inference for low latency and high-fidelity streaming across serving environments, including optimization for Apple silicon.
Design and maintain automated pipelines for model training, evaluation, versioning, and deployment, with special attention to speech, audio, and signal-processing workflows.
Identify and resolve bottlenecks in ML and data workflows, improving system reliability, latency, and throughput at scale.

We are a forward-looking team bringing groundbreaking human interaction into consumer products. We work at the frontier of weak signal sensing and researching their information content, translating fundamental discoveries into transformative technology.

We are looking for a talented researcher with a can-do state of mind, eager to combine psychology, physics, data science, and ML to probe the limits of human interaction. You are passionate about enabling the sensing of weak signals, uncovering their information content, and turning that understanding into real consumer experiences. If you are driven to push the boundaries of what's measurable and translate it into technology the world hasn't seen yet, we want to hear from you.

Responsibilities
Define research topics and strategies aligned with system and product requirements.
Design, build, and operate methods and test setups to quantify system performance.
Design new ways to collect, analyze, and interpret data, translating insights into technology capabilities and product specifications.
Apply existing knowledge to novel approaches to enhance weak signals and compensate for lack of information.
Characterize material and system-level physical limits to inform design feasibility and define system requirements.
Develop and analyze real world experiments to support systems work
Analyze and report results clearly to enable cross-functional teams to make informed design decisions.
Partner with multidisciplinary teams across hardware, software, and systems engineering to drive research from concept to product.

We are seeking a highly skilled and motivated DSP real-time embedded Engineer to join our firmware team. In this role, you will be responsible for implementing cutting-edge digital signal processing algorithms for our next-generation products.

In this role, you will be responsible for implementing cutting-edge digital signal processing algorithms for our next-generation products. You will be a key contributor to the entire product development lifecycle, from concept to deployment, ensuring that our products are intelligent, efficient, and provide a seamless user experience.

Responsibilities
Implement, deploy and optimize real-time DSP algorithms for various sensor data streams (e.g., audio, vision, motion, etc.) on resource-constrained embedded platforms.
Collaborate with algorithm and software teams to integrate DSP algorithms into the firmware.
Profile and optimize code to meet strict performance, power, and memory requirements.
Develop and maintain firmware in C/C++ for embedded systems.
Participate in the entire software development lifecycle, including requirements gathering, design, implementation, testing, and deployment.
Stay up-to-date with the latest advancements in DSP, and embedded systems.

We are seeking a highly skilled and motivated real-time embedded Engineer to join our firmware team.

In this role, you will be responsible for implementing cutting-edge technology for our next-generation products. You will be a key contributor to the entire product development lifecycle, from concept to deployment, ensuring that our products are intelligent, efficient, and provide a seamless user experience.

Responsibilities
Implement, deploy and optimize real-time state machines, operate various sensors streams (e.g., audio, vision, motion, etc.) on resource-constrained embedded platforms.
Design, develop, and maintain real-time firmware for embedded systems.
Optimize code for performance, memory usage, and power consumption.
Develop and execute comprehensive testing strategies for embedded systems.
Develop and maintain firmware in C/C++ for embedded systems.
Work with cross-functional teams including software, hardware, and systems engineers.
Participate in the entire software development lifecycle, including requirements gathering, design, implementation, testing, and deployment.
Stay up-to-date with the latest advancements in embedded systems.

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 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.

The system engineering team is responsible for developing, integrating, and building advanced sensing systems, combining cutting-edge modules with advanced algorithms across multi-disciplinary domains: electro-optical components, unique physical models, bio-mechanical considerations, mechanical and electrical trade-offs, dedicated SW & FW, large-scale data analysis, and classic and ML-based algorithms.

Responsibilities
Own the complete system life-cycle - from Proof-Of-Concept through preliminary design, detailed architecture, module builds, testability, and delivery to mass-production.
Risk mapping and mitigation activities.
Define data collection requirements.
Signal analysis and trade-off mapping.
System optimization.
Collaborate with multiple HW and SW teams to analyze and optimize overall system performance.
Define and track system specifications.
Lead multi-disciplinary teams to deliver reliable, high-performance system features.

We have multiple positions open for Full stack Software Engineers and Senior Full stack Software Engineers to be hired across different Security teams in Israel.

As a Software Engineer you will:
Contribute to business-critical initiatives in our Security.
Use deep technical skills and the ability to quickly adapt to new areas.
Improve the end-to-end lifecycle of services.
Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.
Work on high-end technologies and collaborating across disciplines to deliver impactful features.
Collaborate with multiple teams across us to deliver key customer solutions and support technology.

We are seeking a CAD LEQ (Logical Equivalence Checking) Engineer to develop, deploy, and support equivalence checking methodologies across complex SoC programs. This role focuses on ensuring functional correctness between RTL, synthesized netlists, and post-implementation designs, while driving scalable, robust sign-off flows.

Responsibilities
Own and maintain LEQ sign-off methodology across RTL-to-GDS flows.
Develop and support flows using tools such as Cadence Conformal and equivalent industry solutions.
Drive power-aware equivalence checking including CPX flows.
Enable ECO flows, ensuring safe and correct implementation of late-stage design changes.
Debug equivalence failures and perform root-cause analysis across RTL, synthesis, and PnR stages.
Collaborate with design, synthesis, PD, and power teams to resolve mismatches and improve convergence.
Optimize runtime, capacity, and scalability of LEQ flows for large SoCs.
Define best practices, guidelines, and automation for LEQ usage across projects.
Partner with EDA vendors to resolve tool issues and drive feature improvements.

Join a highly skilled engineering team building core storage infrastructure across multiple system layers. You'll develop and enhance frameworks that handle disk image operations, provide unified storage abstractions, and enable cutting-edge virtualization technologies. This role requires both breadth and depth, comfortable working from kernel-level drivers to user-space frameworks, debugging complex multi-layered systems, and collaborating across hardware, kernel, and application teams. You'll participate in all phases of development: architecture, implementation, optimization, testing, and integration with deeply integrated platform features.

Responsibilities:
Develop kernel-level storage components and user-space frameworks for macOS and our other platforms.
Optimize I/O performance, resource utilization, and power efficiency across the storage stack.
Debug and resolve complex issues spanning hardware, firmware, kernel, and user-space boundaries.
Collaborate with cross-functional teams, including hardware, kernel, filesystem, and virtualization engineers.
Write comprehensive test suites, performance benchmarks, and technical documentation.
Contribute to architecture decisions and long-term technical direction for storage systems.

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

We are seeking a Machine Learning expert to join our wireless FW software group and explore innovative applications of ML algorithms in embedded wireless systems and protocols. This role focuses on cutting-edge research to integrate machine learning into wireless firmware architectures as well as protocol design, validation, and performance optimization. The position emphasizes experimental research, algorithm development, and proof-of-concept implementations in the wireless FW domain. This role offers the opportunity to develop novel solutions that bridge the gap between theoretical machine learning capabilities and practical wireless system implementations.
Responsibilities:
Research & Development: Design, develop, and evaluate machine learning algorithms optimized for real-time wireless communication systems operating under strict real-time, power and computational constraints.
Protocol Innovation: Create novel wireless protocols that intelligently incorporate ML techniques for enhanced performance, efficiency, and adaptability.
Algorithm Optimization: Adapt existing wireless algorithms (e.g. Link Quality, QoS, Scheduling etc) by integrating ML approaches while maintaining real-time performance requirements.
Data Collection & Analysis: Gather, analyze, and curate statistics from existing wireless devices and networks to enable ML model training and validation. Design and implement data collection frameworks for various wireless environments and use cases.
System Integration: Develop lightweight ML models suitable for deployment on resource-constrained wireless devices, including edge computing scenarios.
Performance Analysis: Conduct comprehensive performance evaluations through simulation, theoretical analysis, and experimental validation.
Research Publication: Publish findings in top-tier conferences and journals, and present research at industry conferences.
Collaboration: Work closely with hardware engineers, system architects, and product teams to ensure research translates into practical solutions.
Technology Scouting: Stay current with emerging trends in ML, wireless communications, and edge computing technologies.

As a Wireless Firmware Architect you will focus on defining technical direction, conducting research and analysis, and providing architectural guidance for our Bluetooth embedded solutions.

The position emphasizes wireless protocol design and simulations, software architecture definition, technical planning, proof-of-concept development and performance optimizations.

Responsibilities:
Define comprehensive software architecture for our Bluetooth embedded solutions.
Establish firmware architectural guidelines and principles.
Support development teams with architectural guidance and consultation.
Integrate performance and power analysis requirements into architectural frameworks.
Create technical demonstrations to support architectural decision-making.
Monitor and analyze hardware implementations to ensure alignment with software architectural requirements.
Evaluate hardware design decisions and their impact on firmware architecture.
Collaborate with hardware teams to provide architectural input and recommendations.
Design and develop proof of concept (PoC) projects to validate architectural approaches.
Research and prototype emerging wireless technologies and methodologies.
Evaluate feasibility of new technologies and integration approaches.
Design and develop wireless protocol simulation frameworks, develop intelligent simulation environments for protocol validation and optimization.
Analyze new standards and specifications for architectural implications.
Track industry trends and emerging wireless technologies.

We are a global leader in high-performance smart energy technology, with over 3000 employees, offices in 34 countries, and millions of products installed in over 133 countries. Our diverse product offering comprises intelligent solar inverters, battery Storage, backup systems, EV charging, and complete home energy management ecosystems. By leveraging world-class engineering capabilities and with a relentless focus on innovation, we strive to create a world where clean, green energy from the sun is the primary source of power for our homes, businesses, and just about everywhere we thrive
The IoE group specializes in making our devices smarter and more connected. What You Will Be Doing:
* Develop and design high-quality code following best practices to ensure reliability, maintainability, and scalability.
* Optimize and enhance the performance of existing software components.
* Collaborate with hardware engineers to ensure seamless integration between hardware and software.
* Lead technical discussions, code reviews, and mentor junior engineers.
* Participate in the full software development life cycle including concept, design, development, deployment, and support.
* Leverage cutting-edge AI tools and the latest development features to accelerate development, improve code quality, and drive innovation across the team.
* On the Interface team, you'll develop the core infrastructure handling all communication between the device and external systems - cloud, mobile, and other on-site controllers - deployed across millions of devices worldwide.


Country:
Israel

City:
Herzliya

The Cellular group is seeking a highly skilled Software Engineer to join our team and develop cutting-edge Automation Infrastructure for DevOps and beyond.

In this role, you will contribute to engineering efforts from design to implementation, solving complex technical challenges in multiple areas focusing on CI/CD & SW tool development.

Responsibilities
In this pivotal role, your responsibilities will include:
Design, implement, and maintain CI/CD pipelines for seamless software deployment.
SW Tools development - from idea, requirements definition, the tool's design to its implementation.
Set up infrastructure processes and methodologies to increase the groups efficiency.
Automatic deployment: control and optimize configuration management (with tools such as Ansible, Puppet, or Chef).
Monitor system performance, reliability, and scalability.
Troubleshoot infrastructure and deployment issues, ensuring high availability.
Take part in the optimisation & development of our data path solution.
Working on a varied set of platforms/technologies.