Computer Vision Engineer

Key Skills

Aartificial intelligence, AWS, Azure, C++, Computer Vision (CV), CUDA/GPU programming, Data Analysis, Design, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, OpenCV, Presentation skills, Python Programming

Job Description

What you will do

• Design, develop, and deploy advanced computer vision models, ensuring they are performant and scalable
• Align model development with the practical applications and specific problem domains within the organization
• Enhance existing computer vision algorithms for better accuracy and efficiency
• Explore and implement optimization techniques for model performance improvement in real-world applications
• Conduct exploratory data analysis to discover patterns, anomalies, and insights within the data
• Stay abreast of the latest developments and advancements in computer vision and machine learning
• Collaborate closely with engineers, researchers, and product teams to integrate computer vision capabilities into products and workflows
• Work with product teams to ensure smooth product delivery with high standards, prioritize short-term returns and long-term growth
• Take a creative and strategic approach to solve hard problems. Simplify the complex. Bring in fresh ideas from new places

What you need to have

• Bachelor's Degree and 10 to 12 years of experience; Master's Degree and 8 to 10 years of experience; PhD and 5 to 7 years of experience (in lieu of Bachelor’s degree, 6 additional years of relevant experience)
• Active Top Secret security clearance with SCI eligibility and CI Polygraph
• Proficient experience with machine learning frameworks such as PyTorch, MXNet, or TensorFlow
• Proficient programming skills in Python and C++
• In-depth knowledge of deep learning, covering aspects such as layer architecture, loss functions, optimization techniques, and more
• Hands-on experience in computer vision, image processing, and machine learning, with a demonstrable track record of developing and deploying models into production
• Proven understanding of State-of-the-Art deep learning techniques for computer vision
• Hands-on experience with computer vision libraries such as Scikit-Image, OpenCV, Pillow (PIL Fork), TorchVision, MMCV, Detectron2, and Albumentations
• Knowledge of hardware acceleration libraries like NVIDIA CUDA-X, NVIDIA Performance Primitives, and OpenVINO
• Strong programming and debugging skills
• Problem-solving skills and the ability to think critically and creatively
• Strong communication and presentation skills to convey complex technical concepts to non-technical stakeholders

What we'd like you to have

• Experience with CUDA or other GPU programming languages
• Knowledge of software development best practices, including version control (e.g., Git), unit testing, and continuous integration
• Experience with cloud computing platforms (e.g., AWS, Google Cloud, Azure) for deploying machine learning models. Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying machine learning models
• Publications or contributions to conferences/journals in the field of AI/ML and computer vision
• Active participation in open- source community

About BigBear.ai

BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on BigBear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in Columbia, Maryland, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.