Senior Machine Learning Engineer, Public Sector – AWS Professional Services


  • US
  • Post Date: 16 November 2020
  • Views 29
Job Overview


Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help public sector, medical center, and non-profit customers 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 and DL 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 AI.

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 AI, including building ML or DL 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 Data Scientist position, please feel free to apply. Our Data Scientists can live in any location (D.C, Maryland, Virginia, Illinois, Pennsylvania, New York, New Jersey, Ohio, California) where we have a WWPS Professional Service office. This position will require up to 20% travel as appropriate when allowed.

We’re looking for top 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.

The primary responsibilities of this role are to:
· Design data architectures and data lakes
· Provide expertise in the development of ETL solutions on AWS
· Use ML tools, such as Amazon SageMaker Ground Truth (GT) to annotate data. Work with Professional Services on designing workflow and user interface for GT annotation.
· Collaborate with our data scientists to create scalable ML solutions for business problems
· Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem
· Analyze and extract relevant information from large amounts of historical data — provide hands-on data wrangling expertise
· Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithms
· This position requires that the candidate selected be a US Citizen and obtain and maintain an active TS security clearance.

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
· 5+ years of relevant experience in building large scale enterprise IT systems
· 3+ year of experience with data engineering, ETL, and data wrangling
· 2+ year of public cloud computing experience in AWS


Preferred Qualifications
· Masters or PhD degree in computer science, or related technical, math, or scientific field
· Working knowledge of deep learning, machine learning and statistics.
· User interface experience with Javascript, HTML
· Model deployment experience using C++
· Knowledge of ETL tools and databases (both SQL-based, NoSQL)
· Experience in using Python, R or Matlab or other statistical/machine learning software
· Strong communication and data presentation skills
· The motivation to achieve results in a fast-paced environment.
· Comfortable working in a fast paced, highly collaborative, dynamic work environment

Amazon is committed to a diverse and inclusive workplace.

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