Senior AI Infrastructure Engineer
2 weeks 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 exceptional digital content. We are passionate about enabling creativity and enhancing the way businesses engage with their audiences across various platforms.
We strive to recruit 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 contribute.
Position Overview
We are seeking a strategic and impactful role within our Firefly initiative, which represents a new suite of generative AI models designed to enhance Adobe products. This initiative is a natural progression of Adobe's technological advancements over the past four decades.
Firefly's foundation lies in our commercially viable AI models, meticulously trained on vast collections of images owned or licensed by Adobe. This role offers a unique opportunity to influence millions of creative professionals, assisting them in revolutionizing their workflows.
Key Responsibilities
- Architect, develop, and sustain robust AI/ML infrastructure solutions to facilitate the training and deployment of extensive AI models, utilizing Kubernetes and Python within the AWS cloud environment.
- Enhance and optimize distributed training frameworks that leverage GPU capabilities to boost performance and scalability. Focus on improving resilience, elasticity, data loading, and provide comprehensive support for GPU optimization techniques such as FP8, FSDP, and model parallelism.
- Produce high-quality, maintainable, and testable code that adheres to industry standards.
- Work collaboratively with ML Researchers and Machine Learning Engineers to expedite the training of state-of-the-art ML models.
- Stay informed about the latest advancements in academia and the open-source community to swiftly integrate innovative technologies that enhance ML platform performance.
- Contribute to model improvement by refining orchestration and scheduling, scaling job numbers, and facilitating rapid experimentation through AutoML and similar methodologies.
- Partner with data scientists and ML researchers to optimize the model training pipeline and ensure efficient resource allocation.
- Lead initiatives to innovate infrastructure practices that support groundbreaking machine learning research and development.
Qualifications
- PhD or Master's degree in computer science or a related discipline, accompanied by 5+ years of relevant industry experience.
- Demonstrated expertise in Python and the development of systems, frameworks, and SDKs.
- Solid understanding of infrastructure, model serving, training, orchestration, and GPU resource management.
- Experience with machine learning and distributed PyTorch.
- Strong analytical, critical thinking, and quantitative problem-solving skills.
- Exceptional communication and interpersonal skills, with a collaborative mindset.
Preferred Qualifications
- Familiarity with KubeFlow, MLFlow, Ray, SageMaker, or similar tools.
- Experience with Nvidia HPC.
- Knowledge of PyTorch distributed, MPI, Megatron, Horovod, and other AI training frameworks.
Compensation
Our compensation structure reflects the labor market across various U.S. regions, with salary variations based on location and job-related qualifications. The salary range for this position is competitive and will be discussed during the hiring process.
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 protected characteristic. We welcome applications from qualified individuals with arrest or conviction records in accordance with applicable laws.
Adobe aims to ensure accessibility for all users. If you require accommodations to navigate our website or complete the application process, please reach out for assistance.
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