AWS Lambda (https://aws.amazon.com/lambda) is changing the way that companies big and small think about computing in the cloud. Lambda functions offer customers a "serverless" way to create applications, an approach that lets customers turn business logic and application code into scalable, fault-tolerant production systems without requiring every developer to become an expert in distributed systems, deployment technologies, and infrastructure management.
We are looking for a proven leader to help lead our Applied Science team as we build a team of talented and passionate scientists to leverage the vast amounts of data that millions of Lambda invocations a second generates and use that to both drive business growth opportunities and service efficiency.
We're looking for a leader who combines exceptional technical, research and analytical capabilities to build and lead a team that will be integral to the continued improvement of AWS Lambda. As a Science Manager, you will be responsible for leading a team of researchers and data experts in the design, development, testing, and deployment models to solve challenges like:
· Predicting customer scaling patterns so that Lambda just meets their needs as if by magic.
· Identifying opportunities to more effectively utilize the resources that millions of Lambda functions execute on.
· Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential.
· Providing technical and scientific guidance to your team members.
· Communicating effectively with senior management as well as with colleagues from science, engineering and business backgrounds.
· Supporting the career development of your team members.
Some recent papers the team produced are:
The successful candidate will have an established background in developing analytical models, a strong technical ability, demonstrated experience in people management, excellent project management skills, great communication skills, and the motivation to achieve results in a fast-paced environment.
Inclusive Team Culture
Our team is diverse! We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, Amazon Women and Engineering, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more.
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. This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.
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.
· M.S. or Ph.D. in Research, Computer Science, Applied Mathematics, or a closely related field.
· Proven leadership in NLP or ML. Experience leading and launching ML projects.
· 5+ years of work experience in areas such as data analytics, data modeling, machine learning and large scale simulation.
· Experience in managing and quantifying improvement in multiple business areas resulting from business analytics, optimization techniques, and/or statistical modeling.
· Demonstrated use of modeling and optimization techniques tailored to meet business needs and proven achievements in industrial production systems.
· 3+ years of direct people management experience including duties such as performance evaluation and career development.
· Experience as leader of a science team and developing junior members from academia/industry to a business environment
· Knowledge of various machine learning techniques and key parameters that affect their performance
· Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
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, visit US Disability Accommodations.