Applied Scientist, Amazon, Amazon

Interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence (AI)?

Amazon's Consumer Electronics Technology (CE Tech) organization is redefining shopping experiences leveraging state of the art AI technologies.

We are looking for a talented Applied Scientist with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact.

You will help us shape the future of shopping experiences. As a member of our team, you'll work on cutting-edge projects that directly impact millions of customers, selling partners, and employees every single day.

This role will provide exposure to state-of-the-art innovations in AI / ML systems (including GenAI). Technologies you will have exposure to, and / or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.

The types of initiatives you can expect to work on include :

• Developing personalized recommendation systems that help customers find the right CE products for their needs.
• Creating high quality educational content leveraging complex AI techniques to simplify complex product information.
• Building intelligent automation solutions that generate customized bundles, gift guides and warranties personalization at scale

As a successful applied scientist in the team, you are a well-rounded, analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and machine learning algorithms, can multi-task, and can credibly interface between engineers and business stakeholders.

Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.

This is a fast evolving space, and we are looking for team players that can learn new skills and stretch their technical capabilities to help the team succeed on behalf of our customers.

In this role, you will be able to dive deep into data, discovering root causes, and designing both short-term and long-term solutions.

This candidate will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI.

Key job responsibilities

• Design, implement, and productionalize AI / ML products at Amazon scale, in collaboration with other applied scientists and engineers,
• Develop data architectures, NLP algorithms, and machine learning, deep learning, and Generative AI solutions,
• Use ML tools to annotate data, develop ML / LLM workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc.

and ensure a high bar for the quality of architecture and design of our AIML systems and data infrastructure,

• Leverage AWS AI services and other internal / publicly available external tools & services,
• Be data-driven and possess a quantitative mindset. Grounded, detail-oriented, always backs up ideas with facts. Understand complex application data flows and bridge the gap between technical and business app requirement,
• Analyze and extract relevant information from large amounts of historical data provide hands-on data wrangling expertise,
• Identify state of the art models / solutions to enable new capabilities for code migration and code testing, drive down tech debt and increase operational efficiency,
• Design experiments to evaluate the performance of the model, including analyzing A / B test results to estimate the impact of the model
• Foster a culture of learning & collaboration. Provide thought leadership and hands-on support in selecting, defining, training and fine-tuning Large Language Models (LLMs), prompt engineering, and other GenAI efforts.

We are open to hiring candidates to work out of one of the following locations :

Seattle, WA, USA

BASIC QUALIFICATIONS

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• 1+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
• 1+ years of solving business problems through machine learning, data mining and statistical algorithms experience
• 1+ years of programming in Java, C++, Python or related language experience
• 1+ years of hands-on predictive modeling and large data analysis experience

PREFERRED QUALIFICATIONS

• 3+ years of building machine learning models or developing algorithms for business application experience
• 3+ years of solving business problems through machine learning, data mining and statistical algorithms experience
• 3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• Experience with popular deep learning frameworks such as MxNet and Tensor Flow
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
30+ days ago