Applied Scientist

About the Role

AWS Infrastructure Services Science (AISS) researches and builds machine learning models that influence the power utilization at our data centers to ensure the health of our thermal and electrical infrastructure at high infrastructure utilization. As an Applied Scientist, you will work on our Science team and partner closely with other scientists, data engineers and Software teams to accurately model and optimize our power infrastructure. Outputs from your models will directly influence our data center topology and will drive exceptional cost savings.

Key Responsibilities

• Researching and deploying machine learning models that optimize our power and thermal infrastructure.
• Working across AWS to solve data mapping and quality issues.
• Contributing to our Science team vision.
• Leveraging deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems.
• Disambiguating problems to propose clear evaluation frameworks and success criteria.
• Working autonomously and writing high-quality technical documents.
• Implementing a significant portion of critical-path code, and partnering with engineers to directly carry solutions into production.
• Working closely with other scientists to deliver impactful customer solutions.
• Sharing and publishing works with the broader scientific community through meetings and conferences.
• Communicating clearly to scientific audiences.

Requirements & Tech Stack

• Master's degree.
• Experience programming in Java, C++, Python or related language.
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse.
• Experience building machine learning models or developing algorithms for business application.
• Experience implementing algorithms using toolkits and self-developed code.

Qualifications

• Publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS.
• Experience researching about machine learning, deep learning, NLP, computer vision, data science.
• PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field.
• Superior analytical thinkers, able to quickly approach large ambiguous problems and apply technical and statistical knowledge to identify opportunities for further research.
• Ability to independently mine and analyze data, and use any necessary programming and statistical analysis software.
• Experience in a fast-paced environment that encourages collaborative and creative problem-solving.
• Ability to measure and estimate risks.
• Ability to constructively critique peer research.
• Ability to align research focuses with Amazon’s strategic needs.
• Must be comfortable juggling competing priorities and handling ambiguity.
• Must thrive in an agile and fast-paced environment on highly visible projects and initiatives.
• Need to learn Data Center architecture and components of electrical engineering to build models.