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Senior Applied Scientist, Amazon Forecast (AWS AI)

Job ID: 1826472 | Amazon Dev Center U.S., Inc.

DESCRIPTION

Job summary

Who are we and what we do ?
Amazon Forecast, an applied research team situated within the larger AWS AI organization called AWS AI Labs, is looking to hire a senior applied machine learning (ML) scientist to work on a variety of important applied ML problems in the area of time series modeling. Our applied ML/AI group is entrusted with developing state-of-the-art generalized deep learning based time series models for time series forecasting and anomaly detection.


Who is an ideal candidate ?
You are a technical leader of the science team. You work efficiently and routinely develop the right things with limited guidance. Your work focuses on ambiguous problem areas in existing or new ML initiatives. You take a long-term view of your team's ML solutions and how it fits into the production environment. You understand the business impact of your solutions and you show extreme good judgement when making technical trade-offs between short term technology/operational needs and long term business needs.
As a technical leader of Amazon Forecast science team, you are expected be an expert in the area of time series modeling (forecasting, anomaly detection, change point detection, reinforcement learning). You are expected to maintain an understanding of industry and technology trends in the area of deep learning, temporal point processes, time series modeling. You will be expected to contribute to the larger science community by either giving presentations at workshops, summits, conferences and/or publishing in top-tier conferences.

Inclusive Team Culture
Here 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.

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 and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.








BASIC QUALIFICATIONS

· MS in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
· 3+ years of relevant experience in industry and/or academia.
· 1+ years of experience with a programming language (C++, Java, or similar) and one scripting language (Perl, Python, or similar).
· 1+ years supervised and unsupervised ML approaches and techniques ranging from Regression to Deep Neural Networks.
· 1+ years of successfully applying ML-based solutions to complex problems in business, science, or engineering.
· 1+ years with fast prototyping.
· 1+ years working effectively with software engineering teams.

PREFERRED QUALIFICATIONS

As a Scientist in the AWS AI Lab, you are expected be an expert in an area relevant for large scale machine learning and its applications. Our particular focuses include temporal models particularly for forecasting, anomaly detection and recommendation systems. Experience with deploying ML in practice is a plus.

Preferred qualifications include:
· PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
· 5+ years of relevant experience in industry and/or academia.
· Publications at top-tier peer-reviewed conferences or journals.
· Depth and breadth in state-of-the-art time series modeling and related machine learning technologies.
· Good written and spoken communication skills.
· Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Spark, Hadoop, Map-Reduce).



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.