Sr. Applied Science Manager, AGI Information

Amazon

Seattle, WA

Apply

JOB DETAILS

SKILLS

A/B Testing, Amazon Alexa, Amazon Web Services (AWS), Artificial Intelligence (AI), Best Practices, Career Development, Computer Science, Computer Vision, Conferences, Continuous Improvement, Cross-Functional, Customer Experience, Deep Learning, Documentation, Information Technology & Information Systems, Leadership, Machine Learning, Mentoring, Natural Language Processing (NLP), People Management, Performance Management, Performance Modeling, Problem Solving Skills, Product Engineering, Product Management, Reinforcement Learning, Requirements Management, Statistics, Systems Scalability, Team Lead/Manager, Technical Delivery, Test Data, Testing, Usability Engineering

LOCATION

Seattle, WA

POSTED

4 days ago

Description The AGI Information organization is at the forefront of artificial intelligence and machine learning innovation, developing AI systems used across AWS, Alexa, and other Amazon businesses that transform how customers interact with information, in particular integrating a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques). Our team combines world-class research with production-scale engineering to deliver impactful AI-driven products and services. We're looking for an experienced leader who can drive scientific excellence while building and mentoring high-performing teams of applied scientists and machine learning engineers. If you are deeply familiar with LLMs, natural language processing, and machine learning and have experience managing high-performing research teams, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your team's contributions. It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide! Key job responsibilities * Lead and manage teams of applied scientists and machine learning engineers, providing mentorship, career development, and performance management * Define and execute the technical roadmap for applied science initiatives, balancing innovation with business impact * Work with new technologies and methodologies that improve model performance, usability, and scalability of ML systems * Translate complex business requirements into technical deliverables and deliver operationally stable solutions that provide exceptional customer experiences * Participate in the full development cycle, end-to-end, from research and design to implementation, testing, documentation, delivery, and maintenance * Evaluate and make strategic decisions around the use of new or existing ML frameworks, tools, and technologies * Collaborate with Senior Engineers, Principal Engineers, and Principal Scientists across the organization to define architecture and research plans for the next three years * Drive scientific rigor through experimentation, A/B testing, and data-driven decision making Partner with cross-functional teams including product management, engineering, and business stakeholders to align science initiatives with business objectives * Publish research findings and represent Amazon at top-tier conferences and in the scientific community * Establish best practices for ML development, including model evaluation, monitoring, and continuous improvement Basic Qualifications - 10+ years of building large-scale machine learning and AI solutions at Internet scale experience - Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent) - Experience building large-scale machine learning and AI solutions at Internet scale - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives - Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track Preferred Qualifications - PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent) - Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications - 10+ years of practical work applying ML to solve complex problems for large-scale applications experience - 5+ years of people management experience - Experience leading, mentoring and growing teams of scientists (teams of five or more scientists) 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. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 218,800.00 - 295,900.00 USD annually

About the Company

Amazon

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

COMPANY SIZE

10,000 employees or more

INDUSTRY

Other/Not Classified

FOUNDED

1994

WEBSITE

http://Amazon.com/militaryroles

Resume Resources

Free Resume Templates Free Resume Builder