Amazon

DESCRIPTION

Amazon is seeking an experienced Applied Science Manager to join MIND (Machine Intelligence for Networks and Devices) team within OpsTech Infrastructure Engineering (OTIE) organization to transform our network operations. The vision for OTIE is to be the invisible scaffolding to provide Amazon’s network and device infrastructure for Global Operations. OTIE delivers flexible, low-touch, cost-efficient infrastructure products by leveraging data, analytics, and automation to build a highly scalable and accessible network. If you are passionate about working with big data and thrive in a collaborative, innovative environment, we want to hear from you.

This team of scientists works closely with engineers, product managers, and leadership to invent the future and reshape NetOps (Network management operations).

Key job responsibilities

In this role, you will:

• Lead a team of applied scientists and ML engineers to deliver AI-powered solutions that directly impact product discovery and advertiser success.
• Foster a data-driven culture where hypotheses are tested, insights are derived from robust analysis, and decisions are grounded in evidence.
• Set technical and scientific direction by defining the vision, roadmap, and success metrics for high-impact ML and AI projects.
• Advance scientific excellence by promoting innovation, rigor, and engineering craftsmanship across both science and engineering disciplines.
• Drive execution through planning (sprint, quarterly, and annual), goal-setting, stakeholder alignment, and cross-team collaboration.
• Provide technical guidance and leadership through ambiguous problem spaces, helping the team navigate experimentation, make sound scientific and engineering decisions, and communicate technical results and business impact effectively to senior leadership.
• Mentor and grow talent by hiring top-tier scientists and engineers, and providing ongoing coaching for both career growth and technical development.

A day in the life

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.

The benefits that generally apply to regular, full-time employees include:

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!

At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

BASIC QUALIFICATIONS

• 5+ years of scientists or machine learning engineers management experience
• Knowledge of ML, NLP, Information Retrieval and Analytics
• Experience directly managing scientists or machine learning engineers
• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of industry or academic research experience
• 5+ years of building machine learning models or developing algorithms for business application experience
• Experience hiring and growing top talent
• Experience in applied research

PREFERRED QUALIFICATIONS

• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
• Experience programming in Java, C++, Python or related language

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.