DescriptionExcited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) solutions? Want to help the largest global enterprises derive business value through the adoption of Artificial Intelligence (AI)?
Eager to learn from many different enterprise's use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world's AI technology?
At Amazon Web Services (AWS), we are helping large enterprises build ML models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems.
Our Professional Services organization works together with our AWS customers to address their business needs using ML.AWS Professional Services is a unique consulting team.
We pride ourselves on being customer obsessed and highly focused on the ML enablement of our customers. If you have experience with ML, including building, deploying, and monitoring models, we'd like you to join our team.
You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.This role will focus specifically on AWS' most complex and largest customers in the world to help solve a wide range of business problems.
Consultants will provide deep and broad insight to customers and partners to help remove constraints that prevent them from leveraging AWS services to create strategic value.
A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions.
It will be a person who loves to learn, and wants to innovate in the world of ML.Major responsibilities include : · Understand the customer's business need and guide them to a solution using Amazon SageMaker, AWS AI Services, and Amazon EC2 GPU Instances .
or 5 years of equivalent professional or military experience.· 2+ years of industry experience in ML engineer role.· 4+ years of industry experience in software engineering role.
Portuguese is a plus.PREFERRED QUALIFICATIONS· Master's Degree in a highly quantitative field (Computer Science, Computer Engineering, Statistics, etc.
2+ years of hands-on experience building containerized DevOps pipelines.· 2+ years of relevant experience in building large scale machine learning or deep learning models and / or systems.