Applied Science Manager, Customer Intent

Amazon • Seattle, WA

1d

About The Position

We are seeking an Applied Science Manager to lead the science vision, research strategy, and execution for customer intent modeling that powers next-generation recommendations and personalization. In this role, you will build and mentor a high-performing team of applied scientists, define the multi-year research roadmap, and deliver production-ready models and systems that improve relevance, discovery, and customer trust at scale. The mandate spans modern recommender-system paradigms such as LLM-enabled personalization, intent and journey understanding, representation learning, generative retrieval/ranking, and agentic/conversational experiences grounded in rigorous experimentation and measurable business impact.

Requirements

• 3+ years of scientists or machine learning engineers management experience
• Knowledge of ML, NLP, Information Retrieval and Analytics
• Experience directly managing scientists or machine learning engineers
• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
• 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

Responsibilities

• Own the scientific vision and roadmap for customer intent modeling across the funnel (browse, search, detail-page engagement, add-to-cart, purchase, and post-purchase), translating ambiguous customer problems into a prioritized research and delivery plan.
• Lead and grow a team of applied scientists, including hiring, mentoring, and building a culture of scientific rigor, innovation, and operational excellence.
• Drive end-to-end model and system delivery, partnering closely with engineering to design, implement, launch, and operate solutions in high-throughput, low-latency production environments (candidate generation, ranking, re-ranking, and explanation).
• Advance state-of-the-art personalization using modern techniques (transformers, LLMs, representation learning, reinforcement learning/bandits where appropriate) and ensure research investments translate into measurable lifts via online experiments.
• Establish an evaluation and experimentation strategy for intent and recommendation quality: offline metrics, counterfactual/off-policy evaluation where applicable, calibrated A/B testing, guardrails (trust, safety, fairness).
• Build robust intent representations that capture both short-term intent and longer-horizon preferences, with disciplined approaches to privacy, data minimization, and responsible AI
• Influence product strategy and executive communication, presenting clear scientific narratives, tradeoffs, and decisions to senior leadership and cross-functional stakeholders (product, design, engineering, privacy/legal).
• Raise the scientific bar via external visibility when appropriate: publications, patents, workshops, and internal scientific reviews while balancing novelty with operational impact.

Benefits

• 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
• parental leave

What This Job Offers

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