Tech Stack

Description

You will develop, train, and evaluate computer vision models for geospatial, biometrics, and 3D vision applications. You'll deploy and optimize ML models in production environments and collaborate with scientists and engineers on tasks like object detection and image segmentation. This role involves staying current with research advancements and contributing to mission-critical government projects.

Requirements

• Hands-on experience with computer vision libraries (e.g., OpenCV) and deep learning frameworks (e.g., PyTorch, TensorFlow)
• Proficiency with programming languages such as Python, C/C++ or Rust
• Strong understanding of CNNs, transformers and other advanced architectures and their applications in computer vision tasks
• Strong analytical and problem-solving skills
• Ability to work collaboratively in a team environment and take direction from senior team members
• Hands-on experience with developing computer vision models at scale from inception to business impact
• Design and develop custom/novel architectures, define use cases, and develop methodology benchmarks to evaluate different approaches
• U.S. Citizenship (No Dual citizenship)

Responsibilities

• Develop, train, finetune and evaluate computer vision models in a wide range of topics, including geospatial, biometrics, 3D vision, semantic extraction, etc.
• Deploy, maintain, and optimize ML models and data processes in a production environment
• Develop custom Computer Vision (CV) algorithms that translate into mission value
• Create tools to provide feedback from production ML models and data processes
• Assist in the development and optimization of computer vision models using deep learning frameworks (e.g., PyTorch, TensorFlow).
• Collaborate with other scientists and engineers to build and deploy models for tasks such as object detection, image segmentation, classification, and tracking
• Stay up to date with the latest research and advancements in the field of computer vision and deep learning
• Participate in data collection, preprocessing, and augmentation processes to ensure high-quality datasets
• Conduct experiments, analyze results, and contribute to the improvement of model accuracy and efficiency
• Assist in the integration of computer vision algorithms into production systems and applications
• Document code, methodologies, and experimental results