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

Amazon • Santa Clara, CA

5d

About The Position

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. At AWS Deep Science for Systems & ServicesL you 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. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: - 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 Basic Qualifications: - 10+ years of relevant, broad research experience after PhD degree 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 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.

Requirements

• 10+ years of relevant, broad research experience after PhD degree 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 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.

Nice To Haves

• 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.

Benefits

• Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: Ph.D. or professional degree