Amazon

Machine Learning Engineer II, Measurement and Data Science

Toronto, Ontario Ontario, CA
AWS Scala Spark PyTorch Java Python Machine Learning
Description
- 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
- 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.

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.
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 scale measurement pipelines, as well as advance supporting services and frameworks. You'll get feedback from principal and sr 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.

What we offer
We are a company of builders who bring varying backgrounds, ideas, and points of view to inventing on behalf of our customers. Our diverse perspectives come from many sources including gender, race, age, national origin, sexual orientation, culture, education, and professional and life experience. We are committed to diversity and inclusion and always look for ways to scale our impact as we grow. You can read more here.

Amazon has 13 affinity groups, also known as employee resource groups, which bring Amazon employees together across businesses and locations around the world. Some examples include the Black Employee Network (BEN), Amazon Women in Engineering (AWE), and Indigenous@Amazon.

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 most efficient ways of handling it. closely partner with science team on all aspects, from featurization to training to estimating to knowning we're right. Write code in languages like Scala, Java or Python. Support and improve what you built.

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