Machine Learning Engineer 4

As a Machine Learning Engineer on the SDC team, you will develop and optimize machine learning models and algorithms for search, recommendation, and content understanding across various content types. You'll build and deploy scalable generative AI solutions that power intelligent content discovery and contextual recommendations within Adobe products.

Working closely with cross-functional teams, you will integrate machine learning models into production systems, ensuring performance, reliability, and real user impact. Your day-to-day will include researching, designing, and implementing advanced techniques in natural language understanding, computer vision, and multimodal learning.

You'll be involved across the end-to-end ML pipeline: from data preprocessing and model training to evaluation, deployment, and monitoring. You'll focus on real-time, large-scale applications while driving computational efficiency. In collaboration with product teams, you'll transform user needs into powerful, usable solutions. Additionally, you'll mentor junior engineers and contribute to a culture of excellence and innovation.

What You'll Need to Succeed-

• Bachelor's degree or equivalent experience; advanced degree (Ph.D. preferred) in Computer Science, Machine Learning, Data Science, or a related field
• 6 to 9 years of hands-on industry experience building and deploying ML systems at scale
• Proficient in Python for ML/AI and Java for production-grade systems
• Strong working knowledge of ML frameworks like TensorFlow and PyTorch
• Solid foundation in linear algebra, statistics, optimization, and numerical methods
• Experience with deep learning techniques in areas such as computer vision (CNNs, transformers), natural language understanding (e.g., BERT, GPT), or multimodal AI
• Demonstrated experience delivering production ML solutions with an emphasis on performance and reliability
• Knowledge of distributed systems and frameworks such as Kubernetes, Spark, or Hadoop
• Strong problem-solving skills with a track record of innovative thinking
• Excellent communication and collaboration abilities to thrive in fast-moving, cross-functional environments

Nice-to-Haves

• Experience with generative AI models like Stable Diffusion, DALL·E, or MidJourney, particularly for content generation or discovery use cases
• Familiarity with computational geometry, 3D modeling, or animation pipelines
• Understanding of real-time recommendation systems or large-scale search indexing
• Academic publications in machine learning or related fields