דרושים » תוכנה » software engineer Industrial Automation

Do you have a passion for cutting-edge automotive technology and a desire to work with the world's leading car manufacturers?
We are seeking a highly motivated and technically skilled Software and Automation Tools Engineer to join our team.
Our vision is to bring new and cutting-edge automotive radar sensor solutions, while leveraging our assets and expertise in this field. Introducing best in class Radar sensor that would complement our end-to-end autonomous driving solution platform. You will be joining an excellent group of people, working on a cutting-edge mmWave Radar Technology and enjoy a dynamic and challenging environment.
What will your job look like?
You will be Responsible for high-quality, end-to-end, validation / automation infrastructure & tools
Work on data collection & offline processing SW tools to enable Automotive RADAR development.

We are looking for a Senior Software Engineer to join our software development team, focusing primarily on Lidar calibration software and production line automation. This is a hands-on role where you'll work directly with cutting-edge hardware, develop calibration procedures for the lidar, and contribute to the architecture of mission-critical software systems.

Responsibilities:
Calibration software development: Design, implement, and maintain calibration. procedures working closely with System Engineers.
Production line automation: Develop software solutions to automate manufacturing and testing processes.
Software quality improvement: Enhance code quality, testing frameworks, and development practices across the team.
Architecture & design: Contribute to high-level software architecture decisions and system design.
Cross-functional collaboration: Work closely with hardware, optics, and systems engineering teams.
Team support: Provide backup and knowledge sharing across different calibration procedures and systems.

We are looking for an experienced backend engineer with a background in writing resilient and robust production services. Youre familiar with modern microservices architecture, technologies, and best practices. You have a strong problem-solving attitude and a deep sense of accountability, you are a team player, independent, and most importantly - youre passionate about what you do and about making things better.
We develop event-driven systems and real-time APIs that are used widely across and written mostly in Node.js, Go, and Python. Some of the technologies we work with include: Apache Kafka, K8S, managed AWS services (RDS, CloudFront, Athena, ElastiCache, etc), DataDog, and GraphQL.
What you'll do:
Develop end-to-end services and features, from gathering requirements and research to implementation, deployment, and monitoring.
Integrate and implement AI flows and solutions into the team and department.
Improve quality and find weaknesses in existing processes and services.
Participate in brainstorming and early-stage designs.
Mentor, advise, and work collaboratively within the group, with other development teams, and with all other business teams in the company.
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible.

We are looking for an experienced Senior Algorithm Engineer with expertise in Computer Vision to join our AI team. In this role, you will design, develop, and optimize state-of-the-art vision-based algorithms that power our AI-driven solutions. You will work with large-scale real-world data, contribute to cutting-edge research, and play a key role in bringing advanced AI capabilities to millions of users worldwide.
Responsibilities:
Design, develop, and optimize Computer Vision and Deep Learning algorithms for real-time AI-driven applications.
Work with large-scale visual datasets to train, test, and validate models.
Research and implement state-of-the-art machine learning techniques, including object detection, image segmentation, scene recognition, and 3D processing.
Enhance the efficiency, accuracy, and robustness of existing vision-based models.
Collaborate with software engineers, data scientists, and product teams to integrate algorithms into AI-powered platform.
Stay up to date with the latest advancements in Computer Vision, AI, and Generative Models.

Our patented technology combines autonomous drone hives, computer vision, and AI to deliver actionable insights that uncover new revenue opportunities, reduce operational costs, and enhance safety. Operating in more than 40 countries across 5 continents, were setting the standard for large-scale, data-driven digital transformation.

As a Mobile App Software Developer, you will join our team at the forefront of creating a cutting-edge solution that connects the physical world with the digital one. Your work will directly impact our ability to scale and grow, developing new mobile capabilities and driving innovation. You will tackle interdisciplinary challenges alongside a dedicated team, leveraging sharp problem-solving skills to bring these advanced solutions to production.

You will be responsible for developing world class multi-drone mission software running on mobile devices, flying drones autonomously and connects them with the cloud
You will work end-to-end, writing code for both the mobile app and the server side
Collaborate with an interdisciplinary team for the development of cutting edge software features from inception to release
Work in an Agile team, manage tasks and complete them through TDD, continuous integration as well as modern development processes
Make an impact on the innovation that we bring to drone field operations

We are seeking a skilled ML Engineer to design, build, and deploy advanced ML solutions that drive analytics, anomaly detection, and data classification across enterprise-scale environments.
This role will focus on developing and optimizing models, including LLMs and prompt engineering pipelines, and ensuring seamless integration into production workflows spanning cloud-native, on-premises, and Databricks ecosystems.
Key Responsibilities :
Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.
Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.
Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
Conduct experiments and benchmark results in fast-paced, data-intensive environments.

We are seeking a skilled and motivated Automation Infrastructure Engineer 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.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Key Responsibilities :
Design, build, and maintain efficient and reliable infrastructure 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 talented Algorithm Engineer to join our Cognitive AI team. In this role, you will design, build, and optimize LLM-based agents that power real-time problem solving. You will be hands-on in Python, research-driven, and passionate about creating intelligent, scalable AI solutions that make a real impact.
Responsibilities:
Design, develop, and optimize LLM-based agents for real-world production use cases.
Build intelligent agent frameworks that orchestrate reasoning across tools, APIs, and knowledge bases.
Deploy and maintain LLM applications in production, ensuring performance, scalability, and reliability.
Research new approaches in LLMs and agent architectures, and integrate cutting-edge techniques into production systems.
Collaborate with cross-functional teams (product, engineering, data) to translate business needs into AI solutions.
Continuously monitor and optimize deployed models, diagnosing and resolving bottlenecks.
Think creatively about complex problems and deliver technological Innovation

We are looking for a ML Engineer.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities:
Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.
Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.
Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
Conduct experiments and benchmark results in fast-paced, data-intensive environments.