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Description

Amazon Leadership eXperiences (ALX) Science's mission is to develop science that shapes human behavior in managing Amazon’s talent. We develop the core science for all Amazon-wide talent management and development experiences. Our multidisciplinary science team comprises of applied scientists, data scientists, economists and research scientists. We partner closely with product teams to build scalable science solutions that work backwards from internal customer problems for all of Amazon's businesses and locations around the world. Some of our work includes GenAI-powered writing assistance and insights, talent development and matching recommendations, experimentation and north star metrics, predictive and root cause models for talent events, voice of the customer qualitative analyses frameworks, and talent evaluation framework research.

We are looking for an experienced AI/ML Applied Science Manager who has experience leading teams that build, apply and customize GenAI and traditional ML solutions to solve customer problems in production settings. Techniques we use on the team include NLP, supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning, algorithmic fairness and others on rich and novel datasets.

As a science manager on the team, you will lead a team of ML scientists to build AI/ML solutions to address talent management and development product needs. You will be a hands-on technical leader who excels at driving innovation, fostering a data-driven culture, and leading through ambiguity to deliver measurable impact. You will innovate in the fastest-moving fields of current AI applications, including AI agents and intersection of GenAI and traditional ML systems, such as recommendations, and get to immediately apply your results in highly visible internal Amazon products that have a significant impact on employees’ lives. You will work closely with customers, product and program managers, other engineering managers, and tech leads to understand and guide your teams to build the right solutions. You will develop science roadmaps, communicate your vision and milestones to leadership and to your collaborators in the People Experience and Technology space. If this kind of work excites you, reach out to us to find out more!

Key job responsibilities

- Lead a team of applied scientists to deliver GenAI and ML-powered solutions that directly impact careers of Amazon employees.

- Set technical and scientific direction for the team by defining the vision, roadmap, and success metrics for high-impact GenAI and ML initiatives.

- Drive execution through planning (sprint, quarterly, and annual), goal-setting, stakeholder alignment, and cross-team collaboration.

- Partner with business, product and engineering leaders to define and scope science solutions.

- Mentor and grow talent by hiring top-tier scientists, and providing ongoing coaching for both career growth and technical development.

About the team

ALX Science is an experienced central interdisciplinary organization of scientists spanning machine learning, economics and research that builds science models for Amazon's worldwide employee-facing talent management products, designs and supports experiments for product features, and measures impact of product and program initiatives across the broader organization. Examples of our work include GenAI-powered summarization and writing assistants, content and people recommendation systems, scalable experimentation products and measuring organizational north star metrics.

Basic Qualifications

- 5+ years of building machine learning models for business application experience

- 3+ years of scientists or machine learning engineers management experience

- Knowledge of ML, NLP, Information Retrieval and Analytics

- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

Preferred Qualifications

- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

- Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals

- Experience in applied research

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. 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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.