DESCRIPTION

Are you excited about using decision (optimization), data (ML/DL) and cognitive (AI & LLM) sciences to make multi-million dollar decisions more Data, Science and Analytics Driven? Are you interested in developing smart recommendation and decision engines with Deep Learning, Artificial Intelligence and LLM to enable in-period promotion and long-term financial planning? Do you want to be a part of a multi disciplinary science team focuses on tackling some of the big business problems with within the Devices business at Amazon? Then this could be the role for you!

The Amazon Devices & Services Demand Planning and Product Development (DEPD) team is seeking an outstanding scientist with strong analytical and communication skills to help with machine/deep learning, artificial intelligence and Large Language Models (LLM) to develop automated decision making solutions to manage sales for the entire Amazon device family of products and services. Amazon Devices represents a highly complex space with 100+ products across several product categories that includes Echo, Kindle, Fire Tablets, Amazon TVs, Amazon Fire TV sticks, Ring, and other smart home devices for sale both online and in offline retailers globally.

We develop scalable and robust state-of-the-art HOTW what if scenario planning, recommendation and decision engines that are being supported with complex optimization, machine learning and simulation models.

We are looking for an Applied Scientist with background in Machine Learning, Deep Learning, Artificial Intelligence and Large Language Models who will work on advanced science projects to increase intelligence of recommendation and decision engines with AI (such as reinforcement learning), and explanainability of science models and marketing/sales analysis (such as efficacy of optimization and simulation models) with large language models.

In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impacts. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data, building, managing and improving recommendation, decision and simulation engines, and HOTW decision models, building prototypes and products, and exploring conceptually new solutions, to working with partner teams for prod deployment that will be used primarily for Promotion Optimization and Scenario Planning Capabilities for in-period promotion, and long-term financial planning.

You will collaborate closely with scientists, engineering peers as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services.

You are an individual with outstanding analytical abilities, excellent communication skills, and are comfortable working with cross-functional teams and systems. You will be responsible for researching, prototyping, experimenting, analyzing decision and cognitive models and developing smart automation solutions.

Key job responsibilities
– Research, design, prototype, experiment and implement advanced machine & deep learning, artificial intelligence and generative AI models to address challenging business problems by using modeling languages such as Python; participate in the production level deployment
– Collaborate with cross-functional teams including product management, marketing, and operations to translate model insights into actionable business strategies
– Develop and maintain optimization frameworks, libraries, and tools to enable scalable and efficient optimization capabilities
– Analyze optimization results, identify bottlenecks, and continuously improve the performance and accuracy of optimization models
– Stay up-to-date on the latest academic research and industry best practices in ML/DL, AI and Generative AI and tools, and identify opportunities to apply new approaches
– Create and track accuracy and performance metrics (both technical and business metrics)
– Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders
– Drive best practices on the team; mentor and guide junior members to achieve their career growth potential

A day in the life
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

About the team
The vision for Cognitive Science Team is to deliver science-enabled HOTW demand planning and shaping solutions for Devices Product Lines to support our partners’ decision making processes. We will accomplish our vision by (1) utilizing accelerated applied science with optimization, simulation, scenario planning, Machine Learning and Generative AI (in 2025), (2) performing rapid research & innovation, developing incremental products, and automating processes, (3) developing optimized price and promotion planning, (4) developing high confidence long-lead time marquee unit demand forecasts for Amazon Devices.

BASIC QUALIFICATIONS

– 3+ years of building models for business application experience
– PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience
– Experience programming in Java, C++, Python or related language
– Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
– Strong understanding of machine learning, deep learning, AI and generative AI principles and algorithms, and familiarity with natural language processing (NLP) and computer vision for generative AI applications

PREFERRED QUALIFICATIONS

– Knowledge of architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members
– Experience applying theoretical models in an applied environment
– Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
– Experience in patents or publications at top-tier peer-reviewed conferences or journals
– Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
– Proficiency with modeling and large-scale data processing tools such as Pytorch, scikit-learn, Spark MLLib, PySpark, MxNet, Tensorflow, numpy, scipy etc.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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.

USA, WA, Seattle