Computer Vision Engineer

Position Overview:

• We are looking for an experienced Computer Vision Engineer with practical expertise in the development and deployment of deep learning models for real-time image and video analytics.
• The successful candidate will possess a robust background in computer vision, along with deep learning frameworks and edge deployment solutions.

Main Responsibilities:

• Design, train, and optimize deep learning models for various computer vision applications, including object detection, image recognition, segmentation, and video analytics.
• Oversee large-scale real-time implementations involving up to 100 video streams.
• Refine models such as CNNs and Vision Transformers utilizing frameworks like TensorFlow, PyTorch, and ONNX.
• Create and deploy inference pipelines leveraging NVIDIA technologies, including NGC models, TAO Toolkit, DeepStream, Metropolis, and Triton Server.
• Implement pre-processing and post-processing techniques to enhance model performance and evaluation.
• Develop and execute multi-object tracking algorithms across various camera feeds.
• Conduct camera calibration and extract regions of interest (ROI) for action recognition using temporal analysis methods.
• Construct models for feature extraction and devise strategies for latent space analysis and data manipulation.
• Demonstrated proficiency in writing complex SQL queries; familiarity with NoSQL or Graph Databases, particularly Neo4j, is a plus.
• Knowledge of infrastructure as code tools, such as Terraform and Ansible, is advantageous.
• Experience with containerization technologies like Docker and orchestration tools such as Kubernetes is a plus.

Additional Duties:

• Solid understanding of software configuration management systems.
• Strong business insight, strategic thinking, and cross-industry thought leadership.
• Awareness of cutting-edge technologies and industry trends.
• Logical reasoning and problem-solving abilities, coupled with a collaborative mindset.
• Experience in two or three industry domains.
• Understanding of financial processes related to diverse project types and pricing models.
• Strong client interfacing skills.
• Familiarity with the Software Development Life Cycle (SDLC) and agile methodologies.
• Project and team management capabilities.

Preferred Qualifications:

Technology->AI-Data science->Computer Vision, Technology->AI-Data science->Data Science - Basic, Technology->AI-Generative AI->Artificial Intelligence - BASIC