Applied Science Manager, Data Center Core Network Engineering

DESCRIPTION

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

The Core Networking organization is seeking an experienced Applied Science Manager to lead a team of Scientists, Software Engineers, and Data Engineers in revolutionizing network operations through intelligent automation. In this role, you will define and execute multi-year science strategies to address complex challenges in Network Design, performance scaling, and Operations.

You will lead the production strategy and execution for a diverse range of models (statistical models, GenAI, autonomous agents) in a fast-paced operational environment. This leadership role requires owning machine learning operations and deployment frameworks while building scalable self-service analytics and science infrastructure that enables data driven culture in Core Networking and beyond.

Key job responsibilities
Team Leadership & Development

• Lead and mentor a cross-functional team of applied scientists, data scientists, software engineers, and data engineers
• Hire top-tier talent and provide ongoing coaching for career growth and technical development
• Foster a collaborative, innovative environment aligned with organizational objectives
• Methodically expand the team's domain expertise across diverse science areas

Self-Healing Network Development

• Collaborate with all stakeholder Design and implement autonomous network remediation systems that can take corrective actions with minimal human intervention
• Develop intelligent agents and ML models that collaborate with human network domain experts to identify and resolve network issues
• Build predictive analytics solutions to proactively detect performance issues and anomalies before they impact operations
• Create automated decision-making frameworks that balance autonomous actions with human oversight

Research & Technical Strategy

• Conduct research in GenAI, autonomous agents, LLMs, machine learning, and applied statistics for network operations
• Set technical and scientific direction by defining vision, roadmap, and success metrics for high-impact ML and AI projects
• Stay current with latest developments in network automation and AI-driven operations
• Apply knowledge from multiple disciplines to create innovative solutions for network design, build, and operations optimization

Production & Operations Excellence

• Own machine learning operations and deployment frameworks for production environments
• Support instrumentation and monitoring of production models through A/B test design and validation methods
• Manage suite of production science solutions with infrastructure as code practices
• Deploy science models into service-based application frameworks and embed them into new and existing network products

Cross-Functional Collaboration & Strategy

• Work in ambiguous environments with opportunity to influence and contribute to organizational strategy
• Contribute to complex High-Level-Designs spanning multiple fabric engineering teams
• Provide technical feedback on Low-Level-Designs with deep networking expertise
• Collaborate with stakeholders to define project goals, success criteria, and deliverables
• Communicate complex technical concepts clearly to both technical and business audiences

Project Management & Execution

• Oversee end-to-end lifecycle of data science projects from problem definition to model deployment
• Drive execution through sprint, quarterly, and annual planning with clear goal-setting and stakeholder alignment
• Balance delivering immediate results for operations customers while maintaining focus on long-term science roadmaps
• Navigate experimentation and make sound scientific and engineering decisions in complex problem spaces

A day in the life
You will collaborate with developers, customers, stakeholders, and network domain experts to convert business needs into intelligent, data-driven solutions that make our networks more autonomous and self-healing. You'll support your team in designing and executing science products that can automatically detect network anomalies, predict potential issues, and implement corrective actions. Your days will involve diving deep into network telemetry data, balancing technical execution with longer-term strategy, and growing junior scientists while working closely with engineers, network fabric owners, and leadership to reshape how we design, build, scale, and operate our network infrastructure.

About the team
About AWS

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional

BASIC QUALIFICATIONS

• 5+ years of scientists or machine learning engineers management experience
• Knowledge of ML, NLP, Information Retrieval and Analytics
• 5+ years of building machine learning models or developing algorithms for business application experience
• 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 applied research experience
• Experience programming in Java, C++, Python or related language
• Experience hiring and growing top talent

PREFERRED QUALIFICATIONS

• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
• Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
• Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
• Network domain expertise with understanding of computer and cloud networking challenges across data center network fabrics
• Experience with autonomous systems and intelligent agents for infrastructure management
• Track record of articulating business questions and using quantitative techniques to arrive at solutions using available data
• Proven ability to thrive in ambiguous environments and drive results with minimal support
• Excellent verbal and written communication skills with ability to effectively advocate technical solutions to both technical and business audiences
• Strong organizational and multitasking skills with ability to balance competing priorities across global stakeholder groups
• Experience managing portfolios of projects, resource management, and developing trusted relationships with business stakeholders
• Experience mentoring scientists to improve their skills and efficiency
• Knowledge of structured and unstructured data analysis methodologies for text and numerical data
• Experience with real-time model implementations and production monitoring systems

Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.

IDE statement:
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.