Machine Learning Engineer 2

Adobe's Applied Research team is dedicated to transforming cutting-edge theoretical concepts, particularly in generative AI, into practical, innovative applications that address real-world challenges. This team bridges the gap between research and implementation, leveraging advancements in machine learning, computer graphics, and AI to deliver state-of-the-art solutions. The vision is to continuously evolve and anticipate future industry trends, playing a pivotal role in bringing groundbreaking technologies to market and enhancing user experiences.

Responsibilities:

• Work at the forefront of applying advanced technologies in practical, user-centric applications.
• Implement and optimize generative AI solutions for graphics and design applications.
• Develop sophisticated image processing techniques and enhance human-computer interaction interfaces using machine learning.
• Program in C++ and Python to build robust, production-level software.
• Utilize machine learning frameworks like TensorFlow and PyTorch for model development, conversion, and efficient deployment in production.
• Transform theoretical AI advancements into accessible, efficient, and impactful applications, continuously iterating and improving.
• Engage with computational geometry for 3D modeling and animation innovation, integrating mathematical modeling.
• Push the boundaries of AI technologies and their application in real-world scenarios.

Qualifications:

• 2-4 years of strong industry experience.
• A PhD or a Master's degree in a relevant field (Computer Science, Computer Engineering, Graphic Design, etc.).
• Strong mathematical background, including linear algebra, geometry, and numerical methods, particularly as relevant to graphics.
• Experience or coursework in computer graphics, image processing, human-computer interaction, or machine learning.
• Proficiency in C++ (for in-product development) and/or Python (for machine learning model work) at a production level.
• Proven experience in shipping products to production.
• Knowledge of machine learning and AI techniques, with an emphasis on graphics and design applications.
• Experience with TensorFlow/PyTorch, model conversion, and model deployment to production.
• Publication record in peer-reviewed journals or conferences is a plus.
• Ability to optimize algorithms for performance, especially in real-time applications.
• Strong problem-solving skills and the ability to innovate new solutions.