Computer Vision/Deep Learning Scientist

Job Summary We are hiring multiple Computer Vision / Deep Learning Scientists across various experience levels to support product teams across multiple business units. These roles focus on identifying high-impact business problems and solving them using advanced computer vision and deep learning techniques. Depending on experience level, responsibilities may range from hands-on model development to technical leadership, research direction, and solution architecture.

The ideal candidates are highly technical, collaborative, and research-oriented, with strong experience designing, developing, and deploying computer vision models using modern deep learning frameworks and GPU-based infrastructure.

Key Responsibilities Responsibilities may vary based on level (Scientist, Senior Scientist, or Principal Scientist).

• Collaborate with cross-functional product and engineering teams to define computer vision use cases and translate business problems into technical solutions

• Design, develop, and implement novel computer vision and deep learning algorithms for complex and unique applications

• Build, train, evaluate, and optimize deep learning models for image processing tasks, including:

  • Object detection
  • Image classification
  • Semantic segmentation

• Evaluate model accuracy, performance, and data quality; iterate to improve robustness and scalability

• Conduct research to stay current with emerging computer vision techniques, architectures, and industry best practices

• Utilize and customize convolutional neural network (CNN) architectures such as VGG16, ResNet, MobileNet, and similar models

• Apply traditional image processing techniques using OpenCV, skimage, or related tools when appropriate

• Develop solutions using open-source deep learning frameworks including TensorFlow, Keras, PyTorch, and/or MXNet

• Train and evaluate models on dedicated GPU machines and distributed GPU clusters

• Document technical approaches, experiments, and results; contribute to knowledge sharing across teams

• Monitor deployed models and support ongoing lifecycle improvements

Required Skills & Experience

• Strong proficiency in Python for model development, data processing, and experimentation
• Hands-on experience with TensorFlow, Keras, and/or PyTorch
• Experience with deep learning-based image processing, including classification, object detection, and semantic segmentation
• Familiarity with common CNN architectures (e.g., VGG16, ResNet, MobileNet)
• Experience with traditional computer vision techniques using OpenCV, skimage, or equivalent libraries
• Understanding of model evaluation metrics, data quality, and performance optimization
• Experience working with GPU-accelerated environments and parallel model training
• Strong analytical, problem-solving, and collaboration skills

Experience Levels

• Scientist: Early- to mid-career professionals with hands-on experience developing computer vision models
• Senior Scientist: Advanced practitioners with strong technical depth, solution ownership, and mentoring capabilities
• Principal Scientist: Recognized experts who provide technical leadership, guide research direction, and influence architecture and best practices

Education & Qualifications

• Bachelor's, Master's, or Ph.D. in:

  • Computer Science
  • Electrical Engineering
  • Machine Learning
  • Statistics
  • Or a closely related field

Preferred Qualifications (Optional)

• Experience deploying computer vision models into production environments
• Familiarity with MLOps, model monitoring, and lifecycle management
• Experience working in applied research or R&D-focused teams