Develop systems leveraging CNN-based models and transformer-based vision architectures to analyze, score, and tag photos with metadata

Build models for facial recognition, grouping, and expression analysis

Generate contextual categories for photos, such as portraits, vacations, and events

Evaluate images for aesthetic appeal and print suitability

Create object and scene detection models to extract valuable metadata from photos

Design and prototype custom transformer architectures tailored to product creation needs

Construct scalable pipelines to process large volumes of image data and produce structured, queryable metadata

Integrate image intelligence outputs into downstream applications such as search, ranking, and personalization

Develop and deploy transformer-based machine learning models to analyze user behavior and purchase patterns for personalized product recommendations

Lead experimentation frameworks such as A/B testing to optimize relevance and improve user conversion rates

Build, manage, and maintain the entire machine learning model stack, ensuring seamless deployment and comprehensive system documentation

Collaborate with cross-functional teams to operationalize model development and ensure successful integration into production environments

Communicate effectively with stakeholders and team members while maintaining a self-driven approach to problem-solving

Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or equivalent professional experience

A minimum of 5 years of experience in software engineering or AI/ML-focused roles

At least one year of experience leading and managing development teams

Expertise in computer vision techniques, including CNNs, vision transformers, facial recognition, object detection, image classification, and embedding generation

Strong experience with recommendation systems, collaborative filtering, and deep learning for personalization tasks

Advanced knowledge of transformer-based models for recommendation systems

Proficiency in Python for designing and deploying AI/ML solutions

Practical experience deploying machine learning models at scale using tools such as Docker, AWS, or GCP

Proven ability to lead cross-functional technical initiatives from concept to delivery

In-depth understanding of the machine learning lifecycle, including data management, model evaluation, explainability, and observability

Proficient English communication skills, both written and spoken, at a B2+ level

Familiarity with machine learning libraries such as PyTorch or TensorFlow

Hands-on experience with diffusion models, graph neural networks (GNNs), or reinforcement learning