Amazon SDE II - Machine Learning Amazon Ads Identity 

United States, California, Palo Alto 

543089933

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 ad-serving problems that manifest only at supremely high scale.- Peer with senior engineers and scientists to develop new and innovative ad identity products.- Make data-driven decisions to inform product prioritization.- Be an early adopter of emerging AWS technologies for AdTech use cases.A day in the lifePalo Alto, CA, USA

- 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
- Experience in building machine-learning infrastructure and validating in production
- Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design

- 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 large-scale machine-learning 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