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 diverse content types, including images, videos, pdfs, vector graphics, and so on. You will build and deploy scalable generative AI solutions to enable intelligent content discovery and contextual recommendations within Adobe products. Collaborating with cross-functional teams, you will integrate ML models into production systems, ensuring high performance, reliability, and user impact. Your role will involve researching, designing, and implementing state-of-the-art techniques in natural language understanding, computer vision, and multimodal learning for content and asset discovery. You will also contribute to the end-to-end ML pipeline, including data preprocessing, model training, evaluation, deployment, and monitoring, while pushing the boundaries of computational efficiency to meet the needs of real-time, large-scale applications. Partnering with product teams, you will identify customer needs and translate them into innovative solutions that prioritize usability and performance. Additionally, you will mentor and provide technical guidance to junior engineers and cross-functional collaborators, driving excellence and innovation within the team.

What You'll Need to Succeed-

• Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field
• 6–8 years of industry experience building and deploying machine learning systems at scale
• Proficiency in Python (for ML/AI) and Java (for production-grade systems)
• Strong expertise in ML frameworks and tools such as TensorFlow, PyTorch, etc.
• Solid understanding of mathematics and ML fundamentals, including:
• Linear algebra
• Statistics
• Optimization
• Numerical methods
• Hands-on experience with deep learning techniques in areas such as:
• Computer vision (e.g., CNNs, transformers)
• Natural language understanding (e.g., BERT, GPT)
• Multimodal AI
• Proven ability to deliver ML solutions into production, with focus on performance, scalability, and reliability
• Knowledge of large-scale distributed systems and frameworks such as Kubernetes, Spark, or Hadoop
• Strong problem-solving skills and a mindset for innovation
• Excellent communication and collaboration skills; ability to thrive in a fast-paced, cross-functional environment

Nice-to-Haves

• Experience with Generative AI (e.g., Stable Diffusion, DALL·E, MidJourney) and its application in content creation or discovery
• Knowledge of computational geometry, 3D modeling, or animation pipelines
• Familiarity with real-time recommendation systems or search indexing
• Publications in peer-reviewed journals or conferences in relevant fields