Job description

Are you excited about leading a team of scientists to solve complex, high-impact problems using machine learning and data-driven approaches? At Amazon Advertising Sales, we are looking for an experienced Applied Science Manager who can build, grow, and guide a team that delivers research and production-quality models at scale. In this role, you will own the strategic direction of your team's scientific roadmap, partner closely with business and technical leaders, and ensure your team's work directly shapes important decisions and customer-facing products. You will bridge the gap between science, technology, and business — translating ambiguous challenges into clear research agendas and actionable results. We are specifically looking to build AI agents that can operate accurately at large scale, helping transform the way account teams operate and optimize their end-to-end workflows. We are looking for a deeply scientific leader that brings their expertise in Natural Language Processing, Large Language Models, Reinforcement Learning, Deep learning and/or Recommender Systems to bring exciting new products come to life. If you are a thoughtful, collaborative leader who thrives on turning scientific innovation into measurable impact, we want to hear from you. Key job responsibilities - Lead and manage a team of applied scientists and analysts, setting the strategic direction and roadmap for scientific research that influences organizational goals and annual planning processes. - Partner with business and technical stakeholders to define vision, priorities, and success criteria — ensuring your team builds the right solutions at the right level of fidelity and that final outputs are ready to inform business decisions or move to production. - Evaluate and improve machine learning model accuracy and performance using rigorous experimentation, feature engineering, and hyperparameter optimization, while establishing a team culture focused on reproducibility and scientific rigor. - Hire, develop, and mentor scientists and technical contributors, providing growth opportunities and empowering team members to take ownership of key workstreams and deliver results independently. - Identify opportunities for new analysis, efficiency improvements, and generative AI integration, allocating resources effectively and proactively mitigating risks before they become roadblocks. A day in the life You start your morning reviewing experiment results with your scientists, asking probing questions about model assumptions and business relevance. Mid-morning, you join a cross-functional meeting with engineering and product partners to align on priorities for an upcoming launch. After lunch, you conduct a one-on-one with a team member, coaching them on a new research proposal. Later, you draft a narrative summarizing your team's quarterly progress and outline next steps for leadership review. Throughout, you balance hands-on technical guidance with strategic planning to keep your team delivering high-quality science. About the team Sales AI is focused on applying scientific research and machine learning to solve real problems that matter to Amazon and its advertising customers. We value intellectual curiosity, collaboration, and a commitment to building inclusive, high-performing teams. We believe that great science happens when people with different perspectives work together toward a shared mission. As we continue to grow, you will play a key role in shaping the team's direction, expanding our capabilities, and ensuring our work has lasting impact across the business. - 3+ years of scientists or machine learning engineers management experience - Knowledge of ML, NLP, Information Retrieval and Analytics - PhD, or Master's degree and 6+ years of applied research experience - Knowledge of machine learning approaches and algorithms - Experience building machine learning models or developing algorithms for business application - Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers - Experience with autonomous AI services and associated model development - Experience with sequential recommendation, user intent/mission modeling, or behavioral modeling - Experience with LLM training, fine-tuning, or adaptation (e.g., tokenizer modification, domain adaptation) 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 amazon.jobs for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at amazon.jobs . USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually

Requirements

Must-haves

Key job responsibilities
Lead and manage a team of applied scientists and analysts, setting the strategic direction and roadmap for scientific research that influences organizational goals and annual planning processes.
Hire, develop, and mentor scientists and technical contributors, providing growth opportunities and empowering team members to take ownership of key workstreams and deliver results independently.
Identify opportunities for new analysis, efficiency improvements, and generative AI integration, allocating resources effectively and proactively mitigating risks before they become roadblocks.
A day in the life
About the team
3+ years of scientists or machine learning engineers management experience
Knowledge of ML, NLP, Information Retrieval and Analytics
PhD, or Master's degree and 6+ years of applied research experience
Knowledge of machine learning approaches and algorithms
Experience building machine learning models or developing algorithms for business application
Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
Experience with autonomous AI services and associated model development
Experience with sequential recommendation, user intent/mission modeling, or behavioral modeling
Experience with LLM training, fine-tuning, or adaptation (e.g., tokenizer modification, domain adaptation)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually

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Keywords to mirror

machine learningaimlllm

Platform: amazon
Effort: medium

Benefits

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Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave