Principal Scientist, DevOpsGuru, AWS AI

Key Skills

Java Programming, Design, Python Programming, C++, SQL, Apache Hadoop, Machine learning techniques, SPARK Programming, C# Programming, Data Architecture, Large data sets, Terabyte scale datasets, Data Analysis

Job Description

We are looking for a Principal Applied Scientist for AWS AI Labs, which contributes science and science-related engineering work for Amazon’s cloud-based Artificial Intelligence services (e.g. Amazon DevOpsGuru and new projects already underway). In this role, you will work with your peers and senior management to set direction for Amazon’s AI efforts. Our mission is to put the power of AI in the hands of every developer. You will be responsible for mentoring a team of applied scientists. You will be responsible for creating a strong environment for applied science in order to recruit, retain and develop top talent. You will partner with engineering leaders to deliver remarkable new AWS services and features that leverage Machine Learning and Deep Learning.

As a Principal Applied Scientist, you will identify research directions, create roadmaps for forward-looking research and communicate them to senior leadership, and work closely with engineering teams to bring research to production. You will work with teams of talented scientists, and fill the ranks by attracting the best scientists in applied statistis and machine learning, e.g. anomaly detection, causal inference, timeseries modeling, hypothesis testing. You will work with talented peers and leverage Amazon’s heterogeneous data sources and large-scale computing resources.

Key job responsibilities

• Map business requirements and customer needs to a scientific problem.
• Align the research direction to business requirements and make the right judgments on research/development schedule and prioritization.
• Research, design and implement scalable machine learning (ML), statistical data analysis, or computational models to solve problems that matter to our customers in an iterative fashion.
• Mentor and develop junior applied scientists and developers who work on data science problems in the same organization.
• Stay informed on the latest machine learning, timeseries, anomaly detection, causality and/or artificial intelligence trends and make presentations to the larger engineering and applied science communities.

BASIC QUALIFICATIONS

• PhD/MS degree in electrical and computer engineering, computer science, operations research, statistics, or a related quantitative field.
• 1+ years of hands on experience in working on applied ML problems in an industrial setting.
• Programming experience with at least one modern language such as Python, Java, C++, or C# including object-oriented design.
• Proficiency in model development, model validation and model implementation for large-scale applications.
• 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.

PREFERRED QUALIFICATIONS

• PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
• 10+ years of relevant experience in industry and/or academia.
• Publications at top-tier peer-reviewed conferences or journals.
• Depth and breadth in state-of-the-art computer vision and machine learning technologies.
• Good written and spoken communication skills.
• Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Spark, Hadoop, Map-Reduce).