Senior Software Engineer: Systems Engineer

University of Washington • Seattle, WA

15h • Remote

About The Position

The Cooperative Institute for Climate, Ocean, & Ecosystem Studies (CICOES) is hiring a Senior Software Engineer to design, develop, integrate, test, and deploy software and hardware systems for research applications. The position reports to a Senior Research Scientist and focuses on full-stack solutions for cyber-physical, embedded, and real-time systems, including advanced computer vision, deep learning, object detection, and tracking. The engineer will work with embedded platforms such as Nvidia Jetson Xavier/Orin and use ROS for system integration. The role also contributes to research and development, technical proposals, and peer-reviewed publications.

The engineer will coordinate with UW and CICOES scientists on field deployments, system development, testing, and implementation, and prepare equipment for operation of the KAMERA system. Fieldwork may take place in remote and challenging Arctic environments, including extreme heat and cold and small aircraft operating at low altitude over the ocean. The engineer will troubleshoot systems in the field, develop and monitor solutions, and collaborate with scientists on improving VIAME AI models for species detection and classification, including data-processing challenges such as camera misalignment and duplicate-detection suppression.

The position also coordinates with external partners to integrate imaging systems and hardware with survey aircraft; develop hardware and software for uncrewed aerial systems, including multispectral imaging; and build AI models and cloud-based processing systems and pipelines. Partners include UW and CICOES scientists, NOAA National Marine Fisheries Service Science Centers, the Aircraft Operations Center, other universities, and Kitware. The engineer will help define system performance metrics and requirements, assess aircraft constraints and safety considerations, direct the design and integration of systems, and support operationalization of AI processes and pipelines.

Core technical work includes systems engineering and integration across software nodes, camera drivers, object trackers, distributed hardware, and multimodal data streams; development of software architecture using Python, Bash, ROS, tmux, and Supervisor; computer-vision model training and deployment, including R-CNN-based detectors and EO/IR sensor fusion; and work with 3D vision technologies such as stereo, time-of-flight, laser line scanners, structured light, and structure-from-motion. The engineer will also program and test autonomous vehicles and integrate payloads such as LiDAR and stereo cameras onto UASs, develop cloud-based data-processing solutions using GCP, and lead project and field operations under safety and regulatory frameworks.

This is a permanent, regular, salaried, overtime-exempt position at 100% FTE. It is listed as remote, with office attendance in Seattle when needed. The stated annual pay range is $97,080 to $157,764. The posting refers applicants to the University of Washington benefits information page but does not specify individual benefits.

Requirements

• Bachelor’s degree in computer engineering, computer sciences, software engineering, or a related field; the degree requirement cannot be substituted with equivalent experience.
• At least 5 years of post-graduate professional experience in engineering roles.
• Familiarity with computer vision, including R-CNN architectures, EO/IR sensor fusion, activity recognition, and multimodal camera streams.
• Familiarity with hands-on integration of 2D and 3D vision systems, including stereo, ToF, LLS, and SfM, as well as LiDAR and UASs.
• Programming experience in Python, C++, and Bash.
• Experience working long hours in remote field conditions.
• Experience working on imaging systems in small aircraft.

Nice To Haves

• Expertise in systems engineering, algorithm development, and real-time software solutions.
• Skill integrating hardware and software for advanced applications such as deep learning for image processing, tracking, and detection.
• A proven track record integrating complex software nodes, drivers, and sensors into cohesive platforms.
• Expertise developing and integrating the KAMERA AI-enabled multimodal aerial imaging system.
• More than 5 years of post-graduate professional experience in engineering roles.
• Extensive experience with embedded systems, including Nvidia Jetson platforms.
• Strong Python and C++ programming skills and proficiency with Docker, Git, and Ansible.
• A proven track record working on crewed and uncrewed aerial platforms.
• Experience deploying and testing robotics or vision systems in real-world field environments.
• Experience working long hours in challenging remote field conditions, such as the Arctic.
• Experience working on imaging systems in small aircraft during scientific survey operations over the ocean.
• Experience developing image-processing pipelines in GCP cloud environments.

Responsibilities

• Coordinate with UW and CICOES scientists to plan and schedule fieldwork and coordinate field deployments of data-collection systems.
• Lead system development, testing, and implementation, and prepare field gear and equipment for operating the KAMERA system.
• Troubleshoot technical systems in remote field settings, develop and implement solutions, and monitor systems to verify resolution.
• Collaborate on development and implementation of VIAME AI models for species detection and classification, providing biological and ecological context and addressing data-processing issues such as camera misalignment and duplicate-detection suppression.
• Coordinate with external entities to integrate KAMERA or other imaging systems and hardware with survey aircraft.
• Develop hardware and software for uncrewed aerial systems, including multispectral imaging systems, and develop AI models and cloud-based processing systems and pipelines.
• Collaborate with the Polar Ecosystem Program to establish performance metrics and capabilities for aerial imaging systems, address engineering and troubleshooting needs, and develop cloud-based animal detection and classification solutions for imagery of varying modalities.
• Analyze feedback and metrics from NOAA Fisheries Science Center partners, identify improvement areas, develop solutions, and establish timelines and milestones for system testing and deployment.
• Provide direction to external partners to operationalize AI processes and pipelines.
• Lead development and integration of complex technological systems with aircraft, coordinating with aircraft engineers, pilots, and maintainers and accounting for aircraft capabilities, operational constraints, safety, and flight procedures.
• Direct design and development with external hardware, software, and systems engineering partners for imaging systems, processing pipelines, camera mounts, imagery-analysis software, and field-data collection software.
• Lead systems integration, combining software nodes, camera drivers, and object trackers into cohesive platforms.
• Develop software architecture using Python, Bash, ROS, tmux, and Supervisor across multiple hardware nodes.
• Manage multimodal data streams and create synchronous replay systems for multiple cameras across distributed hardware.
• Work with research scientists to understand data-processing routines and requirements and develop cloud-based solutions using GCP.
• Train and deploy computer-vision models, including R-CNN-based object and person detectors using EO/IR sensor fusion.
• Implement 3D vision technologies and evaluate or use stereo, time-of-flight, laser line scanner, structured-light, and structure-from-motion systems.
• Program and test autonomous vehicles and integrate sensor payloads such as LiDAR and stereo cameras onto UASs.
• Deploy technology in remote field environments and manage real-world testing of vision systems, including work in small aircraft at low altitude over the ocean.
• Lead projects involving complex mechanical and systems engineering under safety and regulatory frameworks such as NRC and DOE requirements.
• Collaborate across research, aircraft engineering, and pilot teams to integrate, test, and deploy systems.

Benefits

• The posting refers to the University of Washington benefits information page; specific benefits are not listed in the job description.
• Opportunities for professional growth.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior