Cleared Computer Vision Scientist

Accenture Federal Services•Washington, DC

91d

About The Position

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company and part of global Accenture, to do work that matters in a collaborative and caring community, where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! The work: 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

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)

Nice To Haves

Advanced Degree in computer science, technology, engineering, mathematics (STEM) related field, with Ph.D. preferred, but not required
Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC
Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP
Hands on experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment
Hands-on experience with other image modalities (SAR, IR, HSI, Lidar, Sonar)
Active Top Secret or TS/SCI or TS/SCI with polygraph Clearance

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