Machine Learning Engineer II, Measurement and Data Science
Come help build ML-based measurement at internet scale. This is a green grass problem without a known answer or a pattern to follow.
What you’ll do
You will design, launch, own and evolve software that computes estimated impact of Amazon ads. Hundreds of thousands advertisers will use your work every day to decide where to invest next. You'll work closely with our top notch team of scientists and economists to invent, build and try ML-based approaches, and iterate on what works best. You'll help define not only how we compute the estimates, but how do we know we're right. These are really hard questions that are unique to Amazon, so there isn't a footprint you can copy. You'll build petabyte-scale measurement pipelines, as well as advance supporting services and frameworks. You'll get feedback from principal and senior engineers, as well as help junior engineers grow.
What we do
We enable advertisers to optimize ad spend and allocate budgets effectively by providing accurate, actionable and timely conversion measurement for all Amazon ad products. We're in the early stages of work, where we invent and try a lot of new approaches. We use a combination of machine learning (ML)-based and deterministic techniques to produce the estimates that are fastest in the industry without compromising quality. We constantly invent on our cutting-edge event-driven architectures to stay ahead of growing scale.
The charter of this team is focused on computing estimated conversions. We own the math, the algorithms, and the design. We work with a variety of technologies, such as AWS EMR, Batch, Scala, Spark and PyTorch. Science is invented in the same team.
Key job responsibilities
• Design, develop, launch and maintain measurement applications that compute accurate estimates of advertising impact.
• Work with the data to understand advertiser needs and develop the most efficient ways of handling it.
• Closely partner with the science team on all aspects, from featurization to training to estimating to knowing we're right.
• Write code in languages like Scala, Java or Python.
• Support and improve what you built.
BASIC QUALIFICATIONS
• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language
PREFERRED QUALIFICATIONS
• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
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, disability, age, or other legally protected status.
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Skills:
Advertising, Algorithms, Amazon Web Services (AWS), Architectural Design, Budgeting, Code Reviews, Coding Standards, Computer Programming, Computer Science, Data Science, Design Patterns Programming Methodologies, Electronic Medical Records, Java, Machine Learning, Mathematics, Needs Assessment, Programming Languages, Python Programming/Scripting Language, Scala Programming Language, Software Administration, Software Development, Software Development Lifecycle (SDLC), Software Engineering, Source Code/Configuration Management (SCM), Testing, Time Management
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 s
Location: Seattle, WA
Posted: Nov. 8, 2024, 9:18 p.m.
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