Sr. Manager, Applied Science, Deep Science Systems & Services

Overview

AWS Deep Science for Systems & Services is looking for a Sr. Manager, Applied Science who will lead a team of world class scientists to work on foundation models, large-scale representation learning, and distributed learning methods and systems. You will lead a team inventing, implementing, and deploying state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions, interact closely with our customers and with the academic and research communities.

You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.

Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets.

• Lead a team of scientists to work on foundation models, large-scale representation learning, and distributed learning methods and systems.
• Invent, implement, and deploy state-of-the-art machine learning algorithms and systems; build prototypes and innovate on new representation learning solutions.
• Interact closely with customers and with the academic and research communities.
• Collaborate with other engineers and scientists in a growing focus area for AWS.
• Contribute to hardware-informed efficient model architectures, training objectives, and curriculum design; participate in distributed training and accelerated optimization methods.
• Engage in continual learning, multi-task/meta learning, reasoning, interactive learning, reinforcement learning, robustness, privacy, and model watermarking; explore model compression, distillation, pruning, sparsification, and quantization.

• Hardware-informed efficient model architecture, training objective and curriculum design
• Distributed training, accelerated optimization methods
• Continual learning, multi-task/meta learning
• Reasoning, interactive learning, reinforcement learning
• Robustness, privacy, model watermarking
• Model compression, distillation, pruning, sparsification, quantization

• 10+ years of relevant, broad research experience after PhD or equivalent.
• Deep expertise in foundational models as well as knowledge of the latest trends in related areas in Machine Learning. Proficiency in programming for algorithm and code reviews.
• Strong core competency in building solutions with a track record of successful projects in algorithm design and product development.
• Publications at top-tier peer-reviewed conferences or journals.
• Strong prior experience with management of senior scientists and engineers.
• PhD in Computer Science, Machine Learning, Mathematics, or related quantitative discipline.
• Expert level skills across many Machine Learning methodologies.
• Published peer-reviewed papers and journals at top-rated academic venues.
• Experience delivering complex end-to-end global ML solutions that run at very big scale.
• Experience with access management and security solutions.
• Effective verbal and written communication skills with non-technical and technical audiences.
• Experience working with real-world data sets and building scalable models from big data.
• Experience thinking strategically and with tactical execution.
• Experience recruiting high caliber talent.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants:
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position.

These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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