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

Develop models for facial recognition, grouping, and expression analysis

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

Assess photos for aesthetic appeal and their suitability for printing

Develop object and scene detection models to extract meaningful metadata from images

Design and prototype advanced transformer architectures tailored to meet product creation needs

Build scalable pipelines to process large datasets and generate structured, queryable metadata

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

Design and deploy transformer-based machine learning models to analyze user behavior and purchasing patterns for personalized recommendations

Lead experimentation frameworks like A/B testing to improve recommendation accuracy and user engagement

Oversee the development, management, and deployment of machine learning models, ensuring robust documentation and seamless integration into production environments

Work collaboratively with cross-functional teams to operationalize model development and ensure successful implementation

Communicate effectively with stakeholders and team members, demonstrating a proactive and self-directed approach

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

At least 7 years of experience in software engineering or AI/ML roles

Minimum of 2 years of experience managing and leading development teams

Participation in at least 2 full-cycle projects or involvement in multiple phases of various development lifecycles

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

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

Advanced knowledge of transformer-based models for recommendation systems

Proficiency in Python for building and deploying machine learning solutions

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

Proven ability to lead cross-functional technical projects from concept to implementation

Comprehensive understanding of the machine learning lifecycle, including data management, model evaluation, explainability, and observability

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

Experience with machine learning libraries like PyTorch or TensorFlow

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