Sde Ii - Palo Alto, United States - A9, Inc.

Description

3+ years of non-internship professional software development experience

• 2+ years of noninternship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language
• Experience in building machinelearning infrastructure and validating in production
• Programming experience with at least one modern language such as Java, C++, or C# including objectoriented design

Are you interested in working with the core Amazon Advertising teams and collaborating with ad tech partners to spearhead innovation and deliver Identity solutions for our customers? Do you want to have direct and immediate impact on millions of customers every day? Do you want to closely work with our experienced scientists to build Machine Learning identity based innovations? We are building the next generation of Identity products and services that will fuel the growth of Amazon's advertising business.

We are looking for self-driven and talented engineers to revel in designing, developing machine learning based identity building and resolution which operates for extremely high volume (internet-scale), low latency systems to drive revenue to Amazon.

Our systems and algorithms operate on internet scale serving advertised products with a high relevance bar and strict latency constraints.

We work hand-in-hand with scientists to come up with novel solutions that deliver highly relevant ads. We consistently strive to improve the identity building and resolution in the ID-less world.

You will drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of Amazon Ads world wide.

This is an opportunity to make a significant impact on the future of the Amazon Ads vision.

As a Software Development Engineer in Machine Learning at Amazon, you will contribute to the technical direction of our offerings and solutions, working with many different technologies across Ads workflows (40+ systems) world wide that integrate with AIP.

You will design, code, troubleshoot, and support scalable machine-learning pipelines and online serving systems.

You will work closely with applied scientists to optimize the performance of machine-learning models and infrastructure, and implement end-to-end solutions.

What you create is also what you own.

Key job responsibilities


In this role, you will:

• You'll build ML based solutions & infra that (1) handles supremely high scale (2) uses known models or optimized modes by collaborating with scientists (3) functions with our highly distributed components and (4) validate them in production WW
• You'll also have an opportunity to partner with our scientists who have years of experience building ML models and experiment in production.
• Solve distributed systems and adserving problems that manifest only at supremely high scale.
• Peer with senior engineers and scientists to develop new and innovative ad identity products.
• Work closely with Product management, business development, scientists and partner teams about new ideas, technical design and project plans
• Make datadriven decisions to inform product prioritization.
• Be an early adopter of emerging AWS technologies for AdTech use cases.
• Think out of the box

A day in the life
You will work collaboratively both within and outside of the Advertising team.

As a Software Engineer, you would spend most of your time architecting, designing and coding and the rest in collaboration and discussion.

Since our team is in US East and West coast, we also like to have fun by taking time to celebrate each other and to spend time with remote happy hours.

About the team

AdTech Identity Program (AIP) team is spearheading innovation for the existential challenges in AdTech today: The need for reliably establishing customer identity in a IDless world without 3P cookies or Device identifiers.

Palo Alto, CA, USA

• 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
• Experience in building largescale machinelearning infrastructure and validating it in production
• Experience with Big Data technologies such as AWS, Hadoop, SageMaker, Hive, etc
• Strong proficiency with Java, Python, Scala or C++
• Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing
• Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practice