Applied Scientist: ML for Data Center Power & Efficiency

Amazon; Newark, Northern (NJ, KY); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

RSUs (restricted stock units)

401(k) matching

Paid time off

Job summary

Amazon is seeking an Applied Scientist for AWS Infrastructure Services Science to develop and deploy machine learning models that optimize data center power and thermal infrastructure. You will work with scientists, data engineers, and software teams to model, validate, and productionize solutions that influence data center topology and cost savings.

You will challenge data quality, sampling biases, and model assumptions, ensuring rigor in data pipelines and code.

Qualifications

• Master's degree required.
• Experience programming in Java, C++, Python.
• 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.
• Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS.

Responsibilities

• Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems.
• Disambiguate problems to propose clear evaluation frameworks and success criteria.
• Work autonomously and write high quality technical documents.
• Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production.
• Work closely with other scientists to deliver impactful customer solutions.
• Share and publish works with the broader scientific community through meetings and conferences.
• Communicate clearly to scientific audiences.

Skills

Java

C++

Python

SQL

Machine learning

Algorithms

Publications

Education

Master's degree

PhD

Job description

Amazon is seeking an Applied Scientist for AWS Infrastructure Services Science to develop and deploy machine learning models that optimize data center power and thermal infrastructure. You will work with scientists, data engineers, and software teams to model, validate, and productionize solutions that influence data center topology and cost savings.

You will challenge data quality, sampling biases, and model assumptions, ensuring rigor in data pipelines and code.