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Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

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Amazon Principal Applied Scientist, Classification & Policy Platform in Seattle, Washington

Description

Ever wonder how you can keep the world’s largest selection also the world’s safest and legally compliant selection? Then come join a team with the charter to monitor and classify the billions of items in the Amazon catalog to ensure compliance with various legal regulations.

We are looking for an outstanding Principal Applied Scientist to be part of the innovation with the state of the art research and technology in Generative AI, LLMs, LMMs. The software we build are a critical component of building a catalog that our customers trust.

You will have an opportunity to work with cutting edge machine learning algorithms on large datasets with unprecedented scale. You will need to build Amazon scale applications running on Amazon Cloud that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data.

As a Principal Applied Scientist, you will be responsible for working across engineering, product, business development, science teams to coordinate deep-dives, inform roadmaps, visualize metrics, and create predictive models to determine how we can best serve our customers.

Key job responsibilities

Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve matching and ranking problems, including filtering, new content indexing, and apply document understanding

Conducting and coordinating process development leading to improved and streamlined processes for model development.

Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps

Providing technical and scientific guidance to your fellow scientists and other team members

Resolve discordant views and bring people together effectively with data and calm approach

Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds

Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers

A day in the life

We are a team of seasoned scientists, engineers and product managers. We work on science problems and publish our results at major conferences while delivering critical product innovations serving Amazon's customers. We work with multiple other science and engineering teams at Amazon.

About the team

We are a tight-knit group that shares our experiences and help each other succeed. We complete one another rather than competing with one another. We love hard problems and like to move fast in a growing and changing industry. We work with unprecedented amount of data and scale which push the boundaries of innovations in the industry. We use data and subject matter experts to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers.

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

Seattle, WA, USA

Basic Qualifications

  • A PhD in Computer Science or similar field

  • Extensive research experience in generative AI, machine learning.

  • 10+ years of hands-on experience in machine learning.

  • Proven record of developing new approaches, algorithms, application areas, etc.

  • Excellent communication skills.

  • Excellent skills in problem solving, programming, and computer science fundamentals.

Preferred Qualifications

  • Extensive experience writing scientific papers, with multiple publications in top machine learning conferences/journals like ICML, ICCV, ICLR, CVPR, ECCV, JMLR, KDD, NeurIPS, PAMI etc.

  • Expertise in generative models, LLMs or machine learning techniques.

  • Experience working in a fast paced, highly collaborative, dynamic work environment.

  • Ability to communicate effectively across multiple organizations in the company.

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 $159,100/year in our lowest geographic market up to $309,400/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.

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