דרושים » הנדסה » Software Engineer - Test Automation

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 skilled and motivated Software Engineer (Automation Infrastructure) to join our team. This role is primarily focused on designing, developing, and maintaining robust automation frameworks and ensuring seamless integration with external systems and partner teams. The ideal candidate will have a strong background in infrastructure automation, excellent problem-solving skills, and a collaborative mindset.
Responsibilities
Design, build, and maintain efficient and reliable automation frameworks.
Implement, test, and bug-fix automation scripts and tools.
Write clean, scalable, and testable code for infrastructure automation.
Participate as a team member in fully agile Scrum deliveries.
Coordinate with other software professionals and developers.
Provide support to end users for automation tools and frameworks.
Collaborate with external teams and third-party vendors to implement integration solutions.
Remain up to date with the terminology, concepts, and best practices in infrastructure automation.

we are looking for a Mobile SDK Engineer.
What youll do:
Develop and maintain mobile SDK features used by developers worldwide
Design and implement reliable and performant SDK components across multiple mobile platforms and operating system versions
Take ownership of end-to-end quality, including design, implementation, testing, and production reliability
Debug and resolve complex issues across different devices, OS versions, and runtime environments
Improve SDK performance, stability, and reliability at scale
Develop and maintain SDK wrappers and integrations for cross-platform frameworks such as Unity, React Native, Flutter, and other mobile environments
Work with modern AI-driven engineering tools, automation systems, and internal developer platforms
Collaborate with engineers across mobile, backend, frontend, and platform teams
Participate in code reviews and contribute to engineering best practices

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).
Proven database experience.
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.

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.

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.

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 looking for a Senior DevOps Engineer with deep expertise in cloud-native platforms to join our global DevOps group and help shape the future of our next-generation SaaS platform
Responsibilities
Collaborate across global R&D teams to manage and evolve a complex, Azure-based production environment powering a cutting-edge data security SaaS platform. 
Build and maintain scalable, resilient, and highly available cloud infrastructure using DevOps practices. 
Design and implement CI/CD pipelines, GitOps workflows, and infrastructure automation using tools like Terraform, Pulumi, Argo CD, and Azure DevOps. 
Work closely with R&D teams to design, implement, and support new product features across the platform. 
Evaluate and adopt emerging cloud-native technologies, open-source tools, and observability platforms to enhance system performance and developer productivity. 
Respond to incidents and internal requests, performing triage, root cause analysis, and implementing solutions to reduce recurrence and resolution time. 
Participate in a 24/7 On-Call rotation to proactively monitor and resolve production issues, ensuring platform stability. 

We are looking for a highly skilled Senior Audio - Voice Processing & Environmental Test Engineer to join our team in Herzliya.

Responsibilities
Test and validate the performance and tuning of core voice processing blocks
Execute validation under diverse acoustic conditions, speaker configurations, and signal scenarios.
Collaborate with algorithm teams to provide data-driven feedback for tuning and optimization.
Conduct objective voice quality assessments using standardized metrics, including POLQA (ITU-T P.863) and PESQ (ITU-T P.862).
Organize and manage subjective "golden ear" listening panels to assess voice naturalness, intelligibility, and overall quality.
Define evaluation criteria and scoring methodologies aligned with industry standards and internal quality benchmarks.
Design and execute WER-based testing for scenarios involving voice transcription and speech recognition.
Correlate WER results with upstream audio processing quality to identify degradation sources.
Conduct testing in specialized laboratories that replicate real-world acoustic scenarios, including: Moving vehicles ,Noisy public environments - cafés, restaurants, crowded spaces Windy outdoor settings and Combined environmental stressors.
Measure and track Time to First Word (TTFW) and round-trip audio latency.
Establish performance baselines and monitoring frameworks for continuous tracking across firmware and software iterations.
Design and maintain automated test suites to detect audio artifacts - including glitches, pops, clicks, distortions, and dropouts.
Build regression frameworks that validate audio quality across new firmware and software updates.