Intern Computer Vision Software Engineering

About the Role

The Computer Vision Software Engineer Intern will join the Software Engineering team supporting TESSA™ Spatial Surgery, Smith+Nephew’s computer-assisted solution for orthopedic surgical navigation. This role offers hands-on experience across image capture and processing, tracking, calibration, geometric computation, and overlay rendering on GPU-accelerated Linux platforms. The intern will deliver a defined, meaningful project, learn how software is developed and verified in a regulated medical-device environment, and gain exposure to the impact of navigation technology in arthroscopy. A hybrid schedule is anticipated.

Key Responsibilities

• Work with experienced mentors to define and complete a focused internship project with a measurable outcome for Smith+Nephew’s navigation software.
• Develop, test, and maintain computer vision features for real-time surgical navigation, including image processing, augmented-reality overlays, and geometric computations.
• Use MATLAB, Python, Julia, or similar tools where appropriate to prototype algorithms, analyze data, or create validation scripts.
• Participate in code reviews, technical documentation, and agile team practices using Git, GitLab, CI, and standardized or containerized development environments.
• Collaborate effectively with colleagues across different locations and time zones.
• Develop C++ skills while learning and applying medical-software practices related to quality, traceability, risk awareness, and verification under the mentorship of experienced engineers.
• Document the project, its results, and key learnings, and present the outcome to engineering stakeholders and senior leadership.

Program Details

• Planned Start Date: May 2027
• Program Length: 12 weeks
• Location: Andover, MA
• Compensation: $27 - $32 USD hourly

Requirements & Tech Stack

• Currently enrolled in an accredited Bachelor’s or Master’s program in Computer Science, Computer Engineering, Electrical Engineering, Biomedical Engineering, Software Engineering, or a closely related field.
• Candidates at approximately the third year of undergraduate study or beyond are encouraged to apply; equivalent project-based experience will also be considered.
• Must be in good academic standing, with a 3.0 minimum GPA preferred.
• Demonstrated programming experience through coursework, academic or personal projects, a prior internship, co-op, part-time role, apprenticeship, or research.
• Programming experience in MATLAB, Python, Julia, C++, or another language through coursework or projects.
• Coursework or project exposure to computer vision or image processing, such as camera models, image filtering, feature detection, multi-view geometry, tracking, or camera calibration.
• Working knowledge of linear algebra and 3D geometry, including rotations, rigid transforms, and projection.
• Exposure to computer vision libraries or software build tools, such as OpenCV or CMake, is a plus.
• Exposure to NVIDIA Jetson, CUDA, Holoscan, or similar GPU or streaming platforms is a plus.
• Familiarity with Eigen, Ceres, optimization methods, point clouds, registration, video pipelines, tracking, or augmented-reality overlays is a plus.

Competencies

• Strong interest in computer vision, medical technology, robotics, augmented reality, or real-time embedded systems.
• Curiosity about surgical navigation and enthusiasm for understanding how software can support arthroscopy workflows and patient care.
• Strong analytical and problem-solving skills, with a practical and methodical approach to experimentation and debugging.
• Ability to design, implement, test, and clearly document software solutions with guidance from experienced engineers.
• Clear written and verbal communication and the ability to collaborate with geographically distributed teams.
• Ability to work independently on defined tasks while seeking feedback and contributing effectively as part of a team.
• High learning agility and motivation to turn academic knowledge into an impactful engineering contribution.