Requirements

Excellent programming skills (Python, C++)
Proven programming skills with standard machine learning tools such as Python, PyTorch, and TensorFlow
Track record of delivering cloud-scale, data-driven products, and services that are widely adopted with large customer bases
Exposure to container runtime environments
Experience in building, deploying, and managing infrastructures in public clouds (AWS, Azure) or virtualization technologies.
Advanced understanding of AI/ML, including ML frameworks
Passion for staying up to date with the latest trends and technologies in AI/ML - in the cloud and on device
Experience with CI/CD tools (e.g., Jenkins, GitLab CI)
Bachelor’s / Masters degree in engineering

Bonus

Experience with GPU optimization (CUDA, Triton)
Experience converting models from various frameworks like PyTorch and TensorFlowto other target formats, to ensure compatibility and optimized performance across different platforms

Design and develop the GenAI backend services for Firefly, creating GPU optimized, efficient model pipelines that power the generative AI features on Firefly website, Photoshop, Illustrator, Express, Stock, and other applications/surfaces
Work on large-scale stateful and stateless distributed systems, Kubernetes, and a wide range of diverse services, including infrastructure, real-time messaging, data ingestion platforms, SQL and no-SQL databases, web services, orchestration services, and more
Collaborate closely with data scientists and engineers to ensure the GenAI services are effectively integrated into Adobe products and systems
Ensure scalable and reliable cloud services with observability, logging, and tracing to enable quick detection, understanding, and resolution of run-time issues
Explore and research new and emerging ML and MLOps technologies to continuously improve Adobe’s GenAI engineering effectiveness and efficiency