Student Veterans of America Jobs

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.

Here are a few things you should know:
  • This site is mobile friendly. You do not need a log-in or password to access information.
  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
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  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.

Job Information

Amazon Senior Applied Scientist, Reinforcement Learning in New York, New York

Description

The Reinforcement Learning (RL) team within Amazon's Supply Chain is at the cutting edge of applying machine learning to real-world problems. We are seeking a talented Senior Applied Scientist with RL experience to join our team. Here you will be focused on making significant contributions to the field, through hands-on research in RL. If you are driven by innovation, we want to hear from you.

In this role you'll have the opportunity to make meaningful advancements in machine learning and AI, contributing to both theoretical and applied aspects of ML and RL.

Key job responsibilities

  • Design, implement, and evaluate innovative models, agents, and software prototypes.

  • Collaborate with a team of experienced scientists to drive technological advancements.

  • Develop novel solutions to complex business problems in collaboration with partner teams.

  • Contribute to Amazon's global science community through collaboration and publication of groundbreaking research.

  • Engage in research projects that contribute to the wider scientific community, sharing findings through publications in top-tier journals and conferences.

A day in the life

As part of our team, you will work alongside thought leaders like Sham Kakade and Dean Foster, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's global inventory planning systems, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines.

You will tackle complex inventory planning challenges using RL, contributing both to the theoretical aspect of the field and its practical applications. We value creative thinking and the ability to approach problems from new perspectives.

About the team

Our team is at the forefront of machine learning research; we are dedicated to developing novel RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is on both advancing theoretical knowledge and implementing these insights to optimize operations and enhance customer satisfaction.

We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operations, managing decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI, our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazon's operations.

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

New York, NY, USA

Basic Qualifications

  • PhD, or Master's degree and 3+ years of applied research experience

  • 2+ years of building machine learning models for business application experience

  • Experience programming in Java, C++, Python or related language

  • Solid track record of research, demonstrated by publication in peer-reviewed conferences or journals, focusing on reinforcement learning, deep learning, and machine learning.

  • Experience in algorithm development.

  • Proficiency in Python or similar, including experience with machine learning frameworks

Preferred Qualifications

  • Expertise in Reinforcement Learning or Machine Learning.

  • Familiarity with the latest trends in Machine Learning.

  • Track record of developing novel algorithms and advancing the state of the art.

  • If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

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 $260,000/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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