Lead Applied Scientist

2 weeks ago

Bellevue, Washington, United States Amazon Full time

Job Overview:

As a part of Amazon's Artificial General Intelligence (AGI) division, our goal is to enhance customer experiences through personalized and context-aware interactions that keep users informed and engaged without overwhelming them.

We are pioneering sophisticated systems designed to provide intuitive and adaptive content recommendations across all Amazon platforms. Our mission is to enable seamless reasoning and improve customer interactions, surpassing the capabilities of traditional machine learning models.

We are in search of a dedicated and innovative Senior Applied Scientist specializing in Natural Language Processing (NLP), Large Language Models (LLM), Recommender Systems, and Information Retrieval. This role involves creating scalable solutions for a cutting-edge context-aware personal assistant.

The ideal candidate will possess a robust background in machine learning and a passion for exploring new frontiers in one or more of the specified areas.

We value individuals who thrive in dynamic settings, are self-driven to tackle complex challenges, and can deliver significant customer impact through rapid experimentation and iterative improvements based on user feedback.

Key Responsibilities:

In your role as a Senior Applied Scientist, you will utilize your technical knowledge and experience to lead efforts in addressing large-scale complex challenges. You will set strategic directions and collaborate with fellow scientists and engineers to develop innovative algorithms and modeling techniques that facilitate timely, relevant, and enjoyable recommendations and interactions.

Your contributions will directly influence our customers through products and services that leverage various machine learning, deep learning, and language model technologies. You will harness Amazon's diverse data sources and extensive computing capabilities to drive advancements in the field.

Basic Qualifications:
  • PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or a related quantitative discipline, or a Master's degree.
  • PhD or Master's degree with 6+ years of applied research experience.
  • 3+ years of experience in developing machine learning models for business applications.
  • Proficiency in programming languages such as Java, C++, Python, or similar.
Preferred Qualifications:
  • PhD in Electrical Engineering, Computer Science, or Mathematics with a focus on natural language processing, recommendation systems, information retrieval, or reinforcement learning.
  • 4+ years of experience in developing machine learning and deep learning models for large-scale customer-facing products or features.
  • Hands-on experience with Large Language Models.
  • Publications in peer-reviewed NLP/ML conferences (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI).
  • Demonstrated scientific thinking and the ability to innovate, with a history of thought leadership and contributions that have advanced the field.
  • Strong software development skills.
  • Excellent written and verbal communication abilities.

Amazon is committed to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status.

For individuals with disabilities who would like to request accommodations, please visit our website for more information.

Amazon offers a comprehensive compensation package that reflects the cost of labor across various US geographic markets. The base salary for this position ranges from $150,400/year in our lowest geographic market to $260,000/year in our highest geographic market. Compensation is determined by several factors, including market location and job-related knowledge, skills, and experience.

Amazon is a total compensation company, and depending on the position, equity, sign-on bonuses, and other forms of compensation may be included as part of the overall package, alongside a full range of medical, financial, and other benefits.

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