Senior Machine Learning Engineer II

At Shutterfly, we make life’s experiences unforgettable. We believe there is extraordinary power in the self-expression. That’s why our family of brands helps customers create products and capture moments that reflect who they uniquely are.

We’re looking for a Senior Deep Learning Engineer with deep knowledge of CNNs and transformer-based vision models to develop intelligent systems across the full lifecycle of our product pipeline: from evaluating and understanding customer photos, to supporting generative product creation, and powering hyper-personalized recommendations. You’ll work with large-scale visual and behavioral datasets—billions of examples rich with metadata—to build models that extract semantic meaning, assess aesthetics and intent, and guide both generative design and recommendation engines. This role spans foundational image modeling, multimodal learning, and personalization, offering a rare opportunity to shape end-to-end AI solutions that directly impact how customers interact with and create meaningful products.

Responsibilities

• Computer Vision & Image Intelligence
• Expertise in CNN based models as well as transformer-based vision models for analyzing, scoring, performing similarity vector analysis and tagging photos with metadata such as:
• Contextual categories (e.g., vacations, events, portraits)
• Aesthetic appeal and print-worthiness
• Area of interest
• Design and prototype custom, next-generation transformer architecture (beyond off-the-shelf models) tailored to Shutterfly product creation needs.
• Develop scalable pipelines for processing large volumes of image data and generating structured, query-able metadata.
• Integrate image intelligence with downstream applications such as search, ranking, and personalization.
• Behavioral AI & Recommendation Systems
• Build and deploy transformer-based ML models that analyze historical user behavior and purchasing patterns to generate personalized product recommendations.
• Lead experimentation frameworks (e.g., A/B testing) to optimize recommendation relevance and conversion.
• Architecture
• Define architectural direction for AI components and ensure their integration with core systems.
  

• 3+ years of experience in Deep Learning focused roles.
• Deep knowledge of computer vision techniques including CNNs, vision transformers, object detection, image classification, and image embedding.
• Proven experience designing and developing custom deep learning models—not just applying off-the-shelf architectures—to solve domain-specific challenges.
• Proficiency in Python and relevant ML libraries (e.g., PyTorch, TensorFlow).
• Experience deploying ML models at scale (e.g., using Docker, AWS/GCP, or similar).
• Proven ability to lead cross-functional technical initiatives from ideation to delivery.
• Strong grasp of ML lifecycle best practices (data management, model evaluation, explainability, observability).
• MSc in Computer Science or related field.
  
  

• Experience with recommendation systems, collaborative filtering, deep learning for personalization, as well as transformer-based models for recommendation systems.
• Hands on experience in diffusion models, graph neural networks (GNNs) or reinforcement learning.