Robotics Application Engineer (Applications & Deployment) (m/f/d)

About The Role

Agile Robots is a dynamic and innovative software development company dedicated to pushing the boundaries of technology. We specialize in creating cutting-edge solutions that transform industries and redefine user experiences.

As we expand our global customer projects, we are seeking a Robotics Application Engineer to join our team.

In this role, you will work on advanced robotics and AI-driven systems. You will contribute to software development and integration for systems involving multi-sensor perception and intelligent decision-making in complex environments. You will collaborate closely with AI teams, robotics engineers, and system architects to build scalable and high-performance software solutions.

At the same time, you will work on customer-facing robotics projects, focusing on application development, system integration, and technical support. You will help bridge product capabilities with real-world deployment, ensuring reliable operation of robotic systems in dynamic environments.

Your Responsibilities

• Design, develop, test, and maintain production software applications.
• Participate in the full software development lifecycle, from requirements analysis to deployment and support.
• Write clean, efficient, and maintainable code following industry best practices.
• Troubleshoot, debug, and resolve software defects and performance issues.
• Contribute to system architecture, code reviews, and continuous improvement initiatives.
• Support deployment, monitoring, and maintenance of software in production environments.
• Ensure software quality through automated testing and adherence to development standards.

Beneficial Skills

• Experience developing and supporting production software systems.
• Develop and maintain low-level camera software, including sensor configuration, camera drivers, device-tree changes, capture-path validation, timestamp handling, metadata handling, and camera control interfaces.
• Experience with agile software development methodologies.
• Efficiency in writing software for embedded applications and sensors.
• Working knowledge of image sensors and imaging pipelines, including Bayer formats, RAW capture, YUV/RGB formats, HDR modes, exposure/gain control, white balance, ISP behavior, and image-quality tradeoffs.
• Proficient with debugging tools and workflows, including kernel logs, tracing, profiling, oscilloscopes or logic analyzers, long-duration test scripts, capture validation tools, and reproducible failure isolation.
• Experience building end-to-end ML training pipelines, evaluation frameworks, and model deployment workflows.
• Strong knowledge of Large Language Models (LLMs), Vision-Language Models (VLMs), and Vision-Language-Action (VLA) models.
• Experience with Transformer architectures, attention mechanisms, multimodal learning, and foundation models.
• Experience with reinforcement learning (RL) and/or imitation learning, including methods such as PPO, DPO, behavior cloning, and offline RL.
• Experience developing and fine-tuning LLMs/VLMs/VLAs, including supervised fine-tuning (SFT), parameter-efficient fine-tuning (LoRA/QLoRA), and preference optimization.
• Knowledge of robot learning and embodied AI, including policy learning, trajectory prediction, action generation, and sim-to-real transfer.
• Experience with dataset creation, data annotation, dataset management, filtering, sampling, and augmentation techniques.
• Experience working with distributed training and GPU acceleration, including CUDA and multi-GPU training.

Qualifications And Requirements

• Master’s degree in Computer Science, Robotics, Software Engineering, or a related field
• Proficiency with C++, Python, HTML, JavaScript, and Linux development
• Experience with Git, containerization (Docker) and collaborative development workflows
• Knowledge of software engineering principles, design patterns, development and methodologies.
• hands-on experience with embedded camera systems, including sensor bring-up, camera module integration, driver-level debugging, and board-level validation.
• Strong proficiency in C/C++ for Linux or performance-sensitive systems, including multithreading, memory management, profiling, and low-latency software design.
• Experience with camera interfaces and supporting hardware, such as MIPI CSI-2, I2C, GMSL, FPD-Link, serializers/deserializers, power sequencing, reset sequencing, clocks, and sensor mode tables.
• Experience developing or modifying Linux camera drivers, device trees, V4L2 drivers, media controller graphs, or similar low-level camera integration components
• Strong understanding of vision requirements for real-time systems, including timestamping, synchronization, buffering, scheduling, latency measurement, jitter reduction, dropped-frame analysis, and deterministic data delivery.
• Experience with multi-camera synchronization, hardware triggering, PTP, PPS, camera-IMU synchronization, or other precise timing systems.

What we offer

• A dynamic high-tech company combined with financial soundness and world-class investors.
• Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.
• Lots of development opportunities in the context of our continued growth.
• Challenging tasks and impactful projects alongside experts that enable professional and personal growth.
• Corporate Benefits Program that covers health, mobility, and learning with 100€ net per month.
• Modern office facilities with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment.

• Experience developing and supporting production software systems.

• Develop and maintain low-level camera software, including sensor configuration, camera drivers, device-tree changes, capture-path validation, timestamp handling, metadata handling, and camera control interfaces.

• Experience with agile software development methodologies.

• Efficiency in writing software for embedded applications and sensors.

• Working knowledge of image sensors and imaging pipelines, including Bayer formats, RAW capture, YUV/RGB formats, HDR modes, exposure/gain control, white balance, ISP behavior, and image-quality tradeoffs.

• Proficient with debugging tools and workflows, including kernel logs, tracing, profiling, oscilloscopes or logic analyzers, long-duration test scripts, capture validation tools, and reproducible failure isolation.

• Experience building end-to-end ML training pipelines, evaluation frameworks, and model deployment workflows.

• Strong knowledge of Large Language Models (LLMs), Vision-Language Models (VLMs), and Vision-Language-Action (VLA) models.

• Experience with Transformer architectures, attention mechanisms, multimodal learning, and foundation models.

• Experience with reinforcement learning (RL) and/or imitation learning, including methods such as PPO, DPO, behavior cloning, and offline RL.

• Experience developing and fine-tuning LLMs/VLMs/VLAs, including supervised fine-tuning (SFT), parameter-efficient fine-tuning (LoRA/QLoRA), and preference optimization.

• Knowledge of robot learning and embodied AI, including policy learning, trajectory prediction, action generation, and sim-to-real transfer.

• Experience with dataset creation, data annotation, dataset management, filtering, sampling, and augmentation techniques.

• Experience working with distributed training and GPU acceleration, including CUDA and multi-GPU training.

• Master’s degree in Computer Science, Robotics, Software Engineering, or a related field

• Proficiency with C++, Python, HTML, JavaScript, and Linux development

• Experience with Git, containerization (Docker) and collaborative development workflows

• Knowledge of software engineering principles, design patterns, development and methodologies.

• hands-on experience with embedded camera systems, including sensor bring-up, camera module integration, driver-level debugging, and board-level validation.

• Strong proficiency in C/C++ for Linux or performance-sensitive systems, including multithreading, memory management, profiling, and low-latency software design.

• Experience with camera interfaces and supporting hardware, such as MIPI CSI-2, I2C, GMSL, FPD-Link, serializers/deserializers, power sequencing, reset sequencing, clocks, and sensor mode tables.

• Experience developing or modifying Linux camera drivers, device trees, V4L2 drivers, media controller graphs, or similar low-level camera integration components

• Strong understanding of vision requirements for real-time systems, including timestamping, synchronization, buffering, scheduling, latency measurement, jitter reduction, dropped-frame analysis, and deterministic data delivery.

• Experience with multi-camera synchronization, hardware triggering, PTP, PPS, camera-IMU synchronization, or other precise timing systems.

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