Location: New York,NY, USA
DESCRIPTION
AWS AI/ML is looking for world class scientists and engineers to join its group working on deploying reinforcement (RL) and machine learning (ML) methods in real-world applications, studying, and building new approaches. Our vision is to advance the state-of-the-art in RL/ML especially as applicability of RL methods has not translated quite well to real world scenarios as they are known to be expensive to train, sample inefficient, sensitive to hyper-parameter settings, and lacking transferability to new tasks. Our team's mission is to study these problems and make RL/ML approaches more robust and reliable. Building these solutions requires a solid foundation in machine learning and reinforcement learning technologies.
We are seeking a Senior Applied Scientist for the team. This is a role that combines science knowledge (around machine learning and reinforcement learning), technical strength, and product focus. It will be your job to develop novel ML/RL systems and algorithms while working with the engineering team to integrate them into different projects. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.
About the team
Inclusive Team Culture
At AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
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. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.
BASIC QUALIFICATIONS
* 3+ years of building machine learning models for business application experience
* PhD, or Master's degree and 6+ years of applied research experience
* Experience programming in Java, C++, Python or related language
* Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
* Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
* Experience in Reinforcement Learning, Web navigation agents, inference time reasoning approaches for LLMs
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
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.