Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.
The ML team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. As an Applied Science Manager in the ML Solutions Lab team, you'll partner with technology and business teams to build new solutions that delight our customers. You will be responsible for leading a team of data/research/applied scientists, deep learning architects, and ML engineers to build machine learning and deep learning models and pipelines, and deliver state-of-the-art solutions to customer’s business and mission problems. Your team will be working with terabytes of text, images, and other types of data to address real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will do all that while yourself maintaining an active personal engagement in the same kind of work at the same kind of high level that you expect from your team.
The successful candidate will possess both technical and customer-facing skills that will allow you to be the technical “face” of AWS within our solution providers’ ecosystem/environment as well as directly to end customers. You will be able to drive discussions with senior technical and management personnel within customers and partners, as well as the technical background that enables them to interact with and give guidance to data/research/applied scientists and software developers.
The ideal candidate will also have a demonstrated ability to think strategically about business, product, and technical challenges. Finally, and of critical importance, the candidate will be an excellent technical team manager, someone who knows how to hire, develop, and retain high quality technical talent.
The primary responsibilities of this position are to:
· Interact with customers directly to understand the business problem
· Lead a team of scientists and engineers, oversee development and research projects at various stages ranging from initial exploration to fully functional and scalable solutions.
· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.
· Work closely with account teams, science teams and product engineering teams to drive model implementations
· Drive new business and product initiatives, championing ideas that move our business forward
· Employ a data driven approach to ensuring the success and outcomes of our ML engagements
This position requires travel of up to 25%. Role can be based in the greater US West region, including San Francisco, San Diego, Los Angeles, Portland, Seattle, Salt Lake City, Phoenix, and Tempe.
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 we 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.
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.
· Masters degree in a quantitative field (economics, computer science, statistics, or equivalent)
· 4+ years of experience applying ML to solve complex problems for large-scale applications
· 2+ years of experience managing data/research/applied scientists, deep learning architects, and ML engineers; successful record of developing junior members to a successful career track
· 2+ years of hands-on experience in programming languages such as Python
· Management experience for working on cross-functional projects
· A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
· 3+ years of experience managing data/research/applied scientists, deep learning architects, and ML engineers
· 3+ years of hands-on experience in modeling and analysis, and in deploying machine learning / deep learning models in production
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Proven track record of innovation in creating novel algorithms and advancing the state of the art
· Entrepreneurial spirit combined with strong architectural and problem-solving skills
· Strong verbal and written communications skills, as well as the ability to work effectively across internal and external organizations. Executive speaking and presentation skills including formal presentations, white boarding, large and small group presentations.
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records