Manager, Machine Learning Solutions Lab

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 Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. As a science manager for the ML Solutions Lab team, you will lead a team of customer-facing scientists and architects to design and deliver advanced ML solutions to solve diverse real-world problems for customers across all industries. You will interact with customers, translate their business problems into ML problems, and lead your team in applying classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.

As part of this team, you will take on challenging, novel problems every day and collaborate with cross-functional teams. You'll need to be comfortable with a degree of ambiguity that’s higher than most projects and love the idea of solving problems that have never been solved before. You will provide thought leadership to technical and business leaders, and have a demonstrated ability to think strategically about business, product, and technical challenges.

The primary responsibilities of this role are to:

- Hire, develop, and lead a diverse, talented team of scientists and architects
- Interact with customers directly to understand the business problem and guide them in their adoption of AI/ML on AWS
- Work closely with cross-functional account, marketing, and product engineering teams to deliver custom ML solutions
- Drive new business and product initiatives, championing ideas that move our business forward

This position requires travel of up to 30%.

About Us

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. 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 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

· Masters or PhD degrees in computer science, engineering, or related technical/scientific field
· 7+ years of professional experience in a business environment
· More than 3 years of experience managing a team of scientists
· Experience in building and delivering machine learning solutions
· Excellent written and spoken communication skills, and strong presentation skills

Preferred Qualifications

· PhD degree in computer science, engineering, or related technical/scientific field
· Scientific thinking and a track record of thought leadership and contributions that have advanced the field
· Strong attention to detail
· Comfortable working in a fast paced, highly collaborative, dynamic work environment
· Business understanding of machine learning as a fundamentally disruptive technical and business strategy

Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, 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