Software Development Engineer, Intern - CV/ML - Military veterans preferred

Eagleview


Locations: Rochester, New York
Categories: Engineering
Job Type: Intern/Co-Op
Work Type: Remote
Req ID: 2546

Job Description

Eagleview® is a leading provider of aerial imagery, property insights and software that transforms the way people work. Eagleview holds more than 300 patents and owns a large geospatial data and imagery library encompassing 94 percent of the US population. Eagleview provides the most accurate data, enabling customers in the government, construction, solar and insurance industries to make timely, informed and better decisions.

EagleView, the leader in aerial imagery, is hiring two passionate Software Development Engineer (SDE) interns in computer vision and machine learning to join its innovative team in the Strategic R&D department. This is an exciting opportunity to work on cutting- edge applications, leveraging the latest advancements in 3D computer vision and machine learning. You will collaborate with a dynamic, talented team to build scalable, secure, and high-performance solutions while contributing to the growth of groundbreaking technologies.

• Support the design, implementation, and testing of features for neural rendering and machine learning-based systems.
• Contribute to code development for 3D reconstruction, optimization, and rendering using techniques such as NeRFs and Gaussian Splatting.
• Assist in optimizing and evaluating model performance, scalability, and accuracy.
• Help deploy models and pipelines on AWS for distributed training and large-scale applications.
• Collaborate with engineers to enhance and maintain CI/CD pipelines and development workflows.
• Write clean, well-documented, and testable code as part of a collaborative development team.
• Participate in code reviews, team discussions, and project planning sessions.
• Stay current with the latest trends and advancements in neural rendering, computer vision, and applied machine learning.

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Vision, Machine Learning, or a related field.
• Solid understanding of machine learning and computer vision fundamentals.
• Proficiency in Python, with some experience using PyTorch.
• Familiarity with AWS and tools used in ML deployment workflows.
• Strong problem-solving skills and attention to detail in technical work.
• Clear and effective written and verbal communication skills for teamwork and documentation.

Preferred Experience:
• Exposure to neural rendering techniques such as NeRFs, Gaussian Splatting, or similar methods.
• Understanding of 3D rendering optimization for real-time or interactive applications.
• Familiarity with 3D reconstruction concepts such as SfM, Multi-View Geometry, or SLAM.
• Basic experience with cloud-based ML workflows or scalable training setups.
• Experience working in agile development environments or collaborative coding practices (e.g., Git, code reviews).

This job description is not an exclusive or exhaustive list of all job functions that a workforce member in this position may be asked to perform. Duties and responsibilities can be changed, expanded, reduced, or delegated by management to meet the business needs of the company.

The compensation offered to the successful candidate will be based on a variety of factors, including but not limited to, the candidate’s work experience, education and licenses, work-related training, key skills, the core duties of the role and its associated responsibilities, and the location where the work will be performed. This is a full time, remote position with a compensation range of $25.00 to $27.00/hr.

As an Equal Opportunity and E-Verify Employer, EagleView Technologies does not discriminate on the basis of any legally protected status or characteristic. Protected veterans and individuals with disabilities are encouraged to apply. We are committed to giving all applicants equal opportunity to participate in the application process and are open to discussing reasonable accommodations for candidates with disabilities.

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