Develop and enhance CNN and transformer-based vision models for image evaluation and scoring

Design and implement custom transformer architectures to support product development

Build robust pipelines to handle high volumes of image data and produce structured metadata

Integrate visual intelligence into applications like search, ranking, and personalization

Deploy transformer-based models for tailored product recommendations

Lead experimentation processes including A/B testing to optimize recommendation quality and conversion rates

Manage and document the complete ML model lifecycle from development to deployment

Collaborate with cross-functional teams to lead technical initiatives from concept through execution

Ensure adherence to best practices in data handling, model assessment, explainability, and monitoring

Extensive software engineering experience with over 5 years focused on AI/ML roles

In-depth expertise in computer vision methods including CNNs, vision transformers, facial recognition, object detection, image classification, and embeddings

Strong background in recommendation systems, collaborative filtering, deep learning personalization, and transformer-based recommendation techniques

Proficiency in Python and ML frameworks such as PyTorch and TensorFlow

Experience deploying machine learning models at scale using Docker, AWS, GCP, or equivalent platforms

Demonstrated leadership in managing cross-functional technical projects from inception to delivery

Comprehensive understanding of ML lifecycle best practices including data management, model evaluation, explainability, and observability

Master’s degree in Computer Science or a related discipline, preferably with a math or physics emphasis

English communication skills at B2 level or above

Practical experience with diffusion models

Knowledge of graph neural networks (GNNs)

Understanding of reinforcement learning concepts