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
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
