ML Engineer, NLP and Search, Public Sector – AWS Professional Services

Amazon
Amazon

  • US
  • Post Date: 18 November 2020
  • Views 24
Job Overview

DESCRIPTION

Excited by using massive amounts of data to develop Machine Learning (ML) models? Want to help government, healthcare, and non-profit customers derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from the many different enterprise use cases of AWS Natural Language and Search capabilities?

At AWS, we are helping large enterprises build ML models in the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. Our Professional Services Data and Machine Learning organization works together with our AWS customers to address their business needs using AI. This role is to work on our team that is specialized in Natural Language Systems, including text and voice, and Search. We’re looking for architects, system, and software engineers capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with building ML models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.

If you do not live in a market where we have an open Machine Learning Engineer position, please feel free to apply. Our Machine Learning Engineers can live in any location (D.C, Maryland, Virginia, Illinois, Pennsylvania, New York, New Jersey, California) where we have a WWPS Professional Service office. This position can have periods of up to 40% travel when allowed and safe.
This position also requires that the candidate selected be a US Citizen and obtain and maintain an active security clearance at the Secret level or higher.

The primary responsibilities of this role are to:
· Design data architectures and data lakes
· Provide expertise in the development of ETL solutions on AWS
· Collaborate with our data scientists to create scalable ML solutions for business problems
· Interact with customers directly to understand their business problems, and assist them in the implementation of their ML ecosystem
· Analyze and extract relevant information from large amounts of data, providing hands-on data wrangling expertise
· Work closely with account team, research scientist teams, and product engineering teams to drive model implementations and new algorithms

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

BASIC QUALIFICATIONS

· BS in computer science or related technical, math, or scientific field
· 2+ years of non-internship professional software development experience
· 2+ years of experience with building ML infrastructure and data pipelines to train models
· Experience with common ML techniques such as pre-processing data, training, and evaluation of classification and regression models
· Experience with Python, R, or other statistical software

PREFERRED QUALIFICATIONS

· Masters or PhD degree in computer science or related technical, math, or scientific field
· 5+ years of industry experience in software development
· 5+ years of experience with big data and scalable model training
· 5+ years of experience with ML in production
· Experience with ML libraries/frameworks such as Tensorflow, Keras, PyTorch, or AWS SageMaker
· Working knowledge of Natural Language Processing, search technologies such as Elasticsearch, or graph databases
· Experience with cloud computing on AWS
· User interface experience with Javascript or HTML
· Strong communication and data presentation skills

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