Robotics Engineer Location: Redmond, Washington Work Arrangement: Onsite / Field-Based Employment Type: Full time Experience Level: Intermediate to Senior – 2+ Years Compensation: Competitive, Based on Experience Position Overview We are seeking a hands-on Robotics Engineer to develop, integrate, deploy, and optimize intelligent robotic systems operating in real-world environments.

This opportunity combines robotics software engineering, machine learning, motion and control systems, hardware integration, and field deployment. The successful candidate will translate robotics research and engineering concepts into reliable, production-capable solutions.

The ideal candidate brings strong Python and/or C++ programming skills, practical ROS/ROS2 experience, familiarity with robotic perception and control, and the ability to troubleshoot integrated hardware and software systems.

We are particularly interested in engineers who enjoy working directly with physical robotic platforms, integrating AI models with sensors and onboard computing hardware, and deploying autonomous capabilities outside controlled laboratory environments. Key

What you will do

Robotics Software Development & Autonomous Systems

- Design, develop, test, and maintain software for autonomous robotic platforms.
- Implement robotics algorithms involving motion control, perception, navigation, and autonomous decision-making.
- Develop robotics applications using Python, C++, and ROS/ROS2.
- Integrate machine learning models and traditional control algorithms into functional robotic systems.
- Build modular software components connecting sensors, perception modules, control systems, and robotic hardware.
- Support robotic learning, autonomous behaviors, and end-to-end execution workflows.

Robotic Hardware & Systems Integration

- Configure and integrate robotic platforms for testing, evaluation, and deployment.
- Connect sensors, onboard computing systems, communication interfaces, and control hardware.
- Configure and troubleshoot robotics middleware, drivers, and hardware interfaces.
- Diagnose integration issues involving embedded computing, sensors, mechanical systems, and software.
- Support deployment across robotic platforms and hardware configurations.
- Ensure reliable operation under practical environmental conditions.
- Deploy machine learning models and autonomous control capabilities onto physical robots.
- Optimize AI workloads for embedded and resource-constrained environments.
- Integrate and evaluate models on NVIDIA Jetson or comparable edge computing hardware.
- Improve inference latency, computational efficiency, responsiveness, and system performance.
- Troubleshoot interactions between robotic control software, AI inference pipelines, and hardware.

Field Testing & Deployment

- Prepare, configure, and validate robotic platforms for field deployment.
- Conduct testing to evaluate reliability, performance, and operational effectiveness.
- Collect and analyze sensor data, system logs, and operating metrics.
- Identify hardware, software, and environmental factors affecting performance.
- Troubleshoot technical issues and implement corrective actions.
- Document testing results,



system limitations, and recommended improvements.
- Support commissioning, customer demonstrations, and ongoing optimization.

Robotics Data Collection & Technical Analysis

- Develop and support data acquisition workflows for robotic sensors and onboard systems.
- Collect and analyze operational data to improve robotic behavior and performance.
- Validate robotics algorithms using measured results.
- Support model evaluation, sensor calibration, and performance analysis.
- Contribute to reproducible testing procedures and reliable data collection processes.

Technical Collaboration & Customer Engagement

- Collaborate with robotics researchers, software engineers, machine learning specialists, and systems engineers.
- Translate research concepts into practical robotic implementations.
- Communicate integration requirements, technical findings, and deployment results.
- Support customer deployments, technical demonstrations, and troubleshooting.
- Document technical solutions and recommend improvements to reliability and scalability.

Required Qualifications Education & Experience

- Bachelor's degree in Robotics, Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering, Mechatronics, or a related discipline, or equivalent practical experience.
- 2+ years of relevant experience in robotics software, autonomous systems, robotic integration, machine learning, or controls engineering.
- Hands-on experience working with physical robotic platforms.
- Experience integrating software with sensors, computing hardware, or robotic control systems.
- Ability to troubleshoot complex hardware/software integration issues.

Programming & Robotics Frameworks

- Strong programming proficiency in Python and/or C++.
- Practical experience with ROS or ROS2.
- Understanding of robotics middleware, nodes, topics, messages, and communication interfaces.
- Experience integrating robotics algorithms and software modules.
- Familiarity with Linux development environments.
- Understanding of robotics software architecture and real-time constraints.

Robotics, AI & Controls

- Understanding of robotic sensing, perception, motion, and control.
- Experience developing or evaluating machine learning models, control algorithms, or autonomous behaviors.
- Familiarity with sensor integration and robotic feedback systems.
- Ability to analyze performance and improve stability, accuracy, and reliability.
- Understanding of embedded computing limitations, latency, and computational requirements.
- Experience configuring, testing, or deploying robotic systems.
- Ability to work directly with hardware, sensors, and embedded computing devices.
- Strong debugging, root-cause analysis, and technical problem-solving skills.




- Effective communication with engineering teams and external stakeholders.
- Willingness to travel to customer or deployment locations when required.
- Current authorization to work in the United States.

Preferred Qualifications Robotics Platforms & Integration

- ROS2 application development and robotic systems integration.
- Experience with robotic manipulators, mobile robots, or autonomous platforms.
- Knowledge of robotic kinematics, manipulation, navigation, or locomotion.
- Sensor integration involving cameras, LiDAR, depth sensors, encoders, or inertial sensors.
- Experience with robotics simulation, virtual testing, or hardware abstraction.
- Experience deploying learned control policies or AI models onto robotic platforms.
- Familiarity with PyTorch or TensorFlow.
- Exposure to reinforcement learning, imitation learning, or learning-based control.
- Computer vision, perception models, or sensor-driven AI applications.
- Vision-language models, robotic learning systems, or AI-driven manipulation.
- Model optimization for embedded and edge environments.

Embedded & Edge Computing

- NVIDIA Jetson or comparable embedded AI platforms.
- GPU acceleration, inference optimization, and embedded Linux.
- Real-time processing and resource management.
- High-throughput sensor data processing.
- Network communication and onboard software deployment.

Testing & Operational Reliability

- Experience deploying robotic systems into industrial, commercial, or customer environments.
- Automated testing, system validation, logging, and monitoring.
- Data collection pipelines and robotics performance evaluation.
- Troubleshooting hardware, firmware, operating systems, and software.
- Version control, collaborative development, and technical documentation.

Ideal Candidate Profile The ideal candidate is a practical robotics engineer who is equally comfortable writing software and working directly with physical machines.

They understand that robotic systems must operate reliably with real sensors, embedded computers, communication interfaces, and unpredictable environmental conditions.

This individual can develop Python or C++ software, integrate robotics components through ROS2, deploy AI models onto embedded hardware, and troubleshoot complete robotic systems.

They enjoy solving complex technical problems, collaborating with researchers, and translating experimental concepts into working autonomous solutions. We value curiosity, independence, strong technical fundamentals, and a genuine interest in advancing real-world robotics.

Core Technical Skills Programming: Python, C++, Linux, Git Robotics: ROS/ROS2, robotics middleware, robotic motion and control, autonomous systems, robotic manipulation, sensor integration, perception, navigation AI & Machine Learning: PyTorch, TensorFlow, robot learning, model inference, computer vision, learned control policies, AI deployment Embedded Computing: NVIDIA Jetson, embedded Linux, GPU optimization, edge AI, real-time processing, sensor data acquisition Systems Engineering: Hardware/software integration, robotic platform configuration, field testing, troubleshooting, debugging, root-cause analysis, performance monitoring

📌 Robotics Engineer (Redmond)
🏢 MeeBoss
📍 Redmond