Manager, Applied Science , Brand Protection ML

Amazon • Seattle, WA

8d

About The Position

Amazon Science gives you insight into the company’s approach to customer focused
scientific innovation. Amazon fundamentally believes that scientific innovation
is essential to being the most customer-centric company in the world. It’s the
company’s ability to have an impact at scale that allows us to attract some of
the brightest minds in artificial intelligence and related fields. Our
scientists continue to publish, teach, and engage with the academic community,
in addition to utilizing our working backwards method to enrich the way we live
and work.

Are you an expert in Computer Vision (CV), Natural Langugage Procesing (NLP) or
Multi-Modality Large Language Models (MLLM)? Are you interested in building
Generative AI solutions on complex business problems that have significant
global benefit. The Brand Protection Science team designs and builds highly
performing and scalable AI models using machine learning, deep learning, LLM/Gen
AI to identify and prevent infringement abuse and counterfeit on behalf of
buyer, seller and brand owners worldwide. As an Applied Science Manager, you
will be lead a group of highly talented scientists, and partner with Tech,
Business and Operations, to build the strategic vision for brand protection,
drive execution and launch scalable AI solutions operating on billions of Amazon
product listings WW for Brand Protection.

Requirements

• 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
• 2+ years of scientists or machine learning engineers management experience
• Knowledge of machine learning approaches and algorithms
• Knowledge of ML, NLP, Information Retrieval and Analytics
• 5+ years of building machine learning models or developing algorithms for business application experience

Nice To Haves

• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
• 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 with the Scrum methodology (or similar alternatives) for agile software development

Responsibilities

• You will lead a team of Applied Scientist to work backwards from customer needs and solve complex scientific problems that have a high business and customer impact.
• As a manager, You will be the thought leader for inventing novel science solutions using SOTA ML techniques including LLM and GenAI.
• You partner with your stakeholders and leadership to define the science vision and strategies for your team.
• You have excellent communication skills to explain complex scientific approaches to a variety of stakeholders and customers, and bridge the gap between science, tech, and business,.
• You are accountable for the science vision and strategic direction of your team, the artifacts they provide, and any technologies owned.
• You will establish structures that enable your team to consistently deliver.
• You will also lead your team to leverage the broader Amazon scientific community, and build a team culture that focuses on bringing research to production, removing road blockers, and delivering more results for Amazon customers.
• You are strategic about the team members' growth and provide those interested with opportunities to demonstrate higher level role scope, impact, complexity and leadership.

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, and parental leave

What This Job Offers

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