Senior Software Engineer - AI and Embedded Systems

The Woods Hole Oceanographic Institution is seeking a Senior Software Engineer to join our AI and Embedded Systems team. This position will focus on the development and implementation of AI and embedded programming systems to help support our cutting-edge oceanographic research and field operations. The successful candidate will have strong skills in Image Machine Learning (ML), Text Mining, Embedded ML, Robotics software engineering, and full-stack development.

Key Responsibilities:

• Design, develop, and maintain AI applications and embedded systems for various oceanographic use cases.
• Collaborate closely with scientists, engineers, and other stakeholders to understand their needs and translate them into functional software.
• Utilize image machine learning and text mining algorithms to extract valuable insights from complex datasets.
• Develop and optimize machine learning models for embedded systems, ensuring they function reliably under real-world conditions.
• Develop and maintain robotics software, with a focus on utilizing the ROS (Robot Operating System) framework.
• Work as part of an interdisciplinary team to test, debug, and improve systems based on user feedback and observed performance.
• Develop full-stack web-based applications.
• Document and communicate technical concepts clearly to both technical and non-technical stakeholders.

Required Qualifications:

• Bachelor's degree in computer science, electrical engineering, robotics, or related field.
• Proficiency in programming languages such as Python, C++, or Java.
• Solid experience in AI and machine learning, particularly with image ML and text mining.
• Experience with embedded systems programming and embedded ML.
• Hands-on experience with robotics software engineering, particularly using ROS.
• Excellent verbal and written communication skills with the ability to clearly express technical concepts to diverse audiences.
• Proven ability to work collaboratively in a team setting, as well as independently.

Preferred Qualifications:

• Familiarity with the unique challenges of oceanographic research and field operations.
• Prior experience in a research institution or a similar role.

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