Machine Learning Engineer - 4

Machine Learning Engineer Focus: From Research to Product | Digital Video & Audio Location: Noida / Bengaluru The Opportunity Adobe’s Digital Video & Audio group develops some of the most innovative and popular creative tools worldwide. These include Premiere, After Effects, and Audition, available on desktop, mobile, web, and cloud. AI is fundamentally transforming how creators imagine, produce, and share content. We’re looking for a passionate Machine Learning Engineer who is excited about turning innovative research into intuitive, reliable product experiences used by millions of creators worldwide. In this position, you will work closely with senior engineers, applied researchers, and diverse collaborators to turn experimental ML prototypes into scalable, production-ready systems. If you enjoy tackling complex machine learning problems in video, audio, and multimodal media — and feel driven by having your innovations incorporated into real products — this is an outstanding chance to create meaningful impact. You will gain hands-on exposure to production-scale ML systems while directly crafting how AI powers Adobe’s creative ecosystem. What You’ll Do Drive the development of ML-powered features from early-stage research prototypes to robust production deployments. Compose, build, and optimize scalable ML pipelines for video understanding, multimodal intelligence, and generative AI applications. Implement, experiment with, and fine-tune brand new deep learning models across Computer Vision, Video AI, and Generative AI domains. Solve real-world creator challenges involving spatial, temporal, and multimodal data. Lead model evaluation, benchmarking, validation, and performance optimization to ensure high quality and reliability. Optimize and deploy models across heterogeneous environments (CPU/GPU/NPU), including ONNX and CoreML workflows. Improve model efficiency through quantization, pruning, distillation, and inference acceleration techniques. Write clean, modular, maintainable, and well-tested production-quality ML code. Collaborate cross-functionally with researchers, product managers, designers, and platform engineers to deliver impactful roadmap-aligned features. Remain updated on emerging ML techniques and actively integrate innovations into video and media workflows. What You’ll Need to Succeed 5+ years of hands-on experience in Machine Learning, Deep Learning, or related domains. Proven experience building, scaling, and deploying ML models in production environments with measurable impact. Strong proficiency in PyTorch (preferred) or TensorFlow, and Python-based ML development. Solid foundations in mathematical modeling, including Linear Algebra, Probability, Statistics, and optimization theory. Deep understanding of core ML principles: model training, validation, generalization, and performance trade-offs. Strong grasp of deep learning architectures including CNNs, RNNs, Transformers, and multimodal models. Clear understanding of when and why to apply each architecture for spatial, temporal, or cross-modal tasks. Practical experience in computer vision tasks such as object detection, segmentation, tracking, video understanding, or temporal modeling. Familiarity with model optimization and deployment techniques including pre/post training quantization, ONNX, CoreML, and edge deployment. Understanding of software engineering guidelines including version control (Git), testing frameworks, CI/CD, and code review processes. Strong analytical thinking, problem-solving ability, and curiosity to learn in a fast-evolving AI landscape. Excellent communication skills and the ability to collaborate effectively within diverse, high-performing teams. Why You’ll Love This Role Develop AI systems that support millions of creators around the world. See your ideas move from research to real-world impact. Collaborate with world-class engineers and researchers. Address significant, large-scale ML challenges in video and media. Grow in ... (truncated, view full listing at source)