Research Engineer II

EagleView•Remote US, UNAVAILABLE

3h•Remote

About The Position

The Research Engineer II in the Strategic R&D department plays a key role in exploring, developing, and transitioning cutting-edge technologies from research concepts to scalable products. 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.

Requirements

BSc/MSc/PhD in Computer Vision, Computer Science, or related fields.
Solid knowledge of machine learning, deep learning, and computer vision principles.
Proficiency in Python and PyTorch, with experience implementing complex neural networks.
Experience training, deploying, and running models with AWS or other cloud platforms.
Strong problem-solving and analytical skills, with the ability to handle complex challenges.
Excellent written and verbal communication skills for technical documentation and collaboration.

Nice To Haves

Prior experience with NeRFs, 3DGS, or similar neural rendering technologies.
Familiarity with 3D reconstruction techniques such as Multi-View Geometry, SfM, and SLAM.
Experience working with aerial/satellite imagery, photogrammetry, or geospatial datasets.
Experience with Docker and containerized application development.
Experience in agile software development methodologies.

Responsibilities

Design, implement, test, and document new features for 3D Computer Vision and machine learning-based systems.
Develop algorithms for 3D reconstruction, optimization, and rendering using point clouds, meshes, NeRFs, and Gaussian Splatting.
Conduct experiments to improve model performance, scalability, and accuracy.
Assist in deploying models and pipelines on AWS for distributed training and large-scale applications.
Stay updated with the latest research and trends in neural rendering, computer vision, and machine learning.