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Senior AI Infrastructure Engineer
2 months ago
About Adobe
At Adobe, we are dedicated to transforming the world through innovative digital experiences. Our mission is to empower individuals—from budding creators to established brands—with the tools they need to craft and deliver outstanding digital content. We are passionate about enabling creativity and enhancing the way businesses engage with their audiences across various platforms.
We strive to attract top talent and foster an inclusive workplace where every employee is valued and has equal opportunities. We believe that great ideas can emerge from any level of the organization, and we are excited to see what you can bring to the table.
Position Overview
We are excited to introduce Firefly, our latest suite of generative AI models designed to revolutionize content creation within Adobe products. This initiative represents a natural progression of the innovative technology we have developed over the past four decades.
At the heart of Firefly are our commercially viable AI models, meticulously trained on vast collections of images that are either owned or licensed by Adobe. We are seeking a strategic and impactful role to help advance these models, providing a unique opportunity to influence millions of creators and reshape their workflows.
Key Responsibilities
- Architect, develop, and sustain robust AI/ML infrastructure solutions that facilitate the training and deployment of large-scale AI models, utilizing Kubernetes and Python on AWS cloud.
- Enhance and optimize distributed training frameworks that leverage GPUs to boost performance and scalability. Focus on improving resiliency, elasticity, data loading, and providing comprehensive support for GPU optimization techniques such as FP8, FSDP, and model parallelism.
- Produce high-quality, maintainable, and testable code adhering to industry best practices.
- Collaborate closely with ML Researchers and Machine Learning Engineers to expedite the training of state-of-the-art ML models.
- Stay abreast of the latest advancements in academia and the open-source community to facilitate the swift adoption of cutting-edge technologies that enhance the performance of the ML platform.
- Contribute to the improvement of model training by refining orchestration and scheduling, scaling job quantities, and accelerating experimentation through AutoML and similar methodologies.
- Work alongside data scientists and ML researchers to optimize the model training pipeline and ensure efficient resource utilization.
- Drive innovation in infrastructure practices to support groundbreaking machine learning research and development.
Qualifications
- PhD or Master's degree in computer science or a related discipline, with a minimum of 5 years of relevant industry experience.
- Demonstrated expertise in Python and experience in developing systems, frameworks, and SDKs.
- Solid understanding of infrastructure and experience with model serving, training, orchestration, and GPU resource management.
- Familiarity with machine learning and distributed PyTorch.
- Strong analytical, critical thinking, and quantitative problem-solving skills.
- Excellent communication and interpersonal skills, with a collaborative mindset.
Preferred Qualifications
- Experience with KubeFlow, MLFlow, Ray, SageMaker, or similar tools.
- Experience with Nvidia HPC.
- Familiarity with distributed PyTorch, MPI, Megatron, Horovod, and other AI training frameworks.
Compensation and Benefits
Adobe offers competitive compensation that reflects the labor market across various U.S. regions. The annual salary range for this position is $170,900 to $325,200, with variations based on work location and job-related knowledge, skills, and experience.
Adobe is committed to equal employment opportunities and affirmative action. We do not discriminate based on gender, race, ethnicity, age, disability, religion, sexual orientation, gender identity, veteran status, or any other characteristics protected by law. We aim to create an accessible environment for all users.
