Machine Learning Engineer, AI/ML Practice

Key Skills

HTML, JavaScript, Java Programming, Python Programming, SQL, AWS, Machine learning techniques, MATLAB Programming, NoSQL, R Programming, ETL frameworks, Geospatial Statistical

Job Description

Job summary
Are you excited to help the Intelligence Community to leverage massive amounts of data in developing Machine Learning (ML) and Deep Learning (DL) models and adopting 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 the federal government 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 love 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.

In this role, you will be able to dive deep into data, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI.

Major Responsibilities include:

• Design data architectures and data lake
• Provide expertise in the development of ETL solutions on AWS
• Use ML tools such as to annotate data. Work with our data scientist on designing AI workflow and end-to-end pipelines.
• 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 can have periods of up to 10% travel
  This position requires that the candidate selected be a U.S. citizen, must currently possess and maintain an active TS/SCI security clearance with polygraph. In compliance with the U.S. government requirement that employees of its contractors, and employees who work on or in connection with U.S government contracts must receive the COVID-19 vaccine, this position may require that the candidate selected be fully vaccinated against COVID-19. A person is considered fully vaccinated by completing the full regimen of the COVID-19 vaccine (two doses for Pfizer or Moderna and one dose for Johnson & Johnson).
  
  For more information please contact Renee Taylor at tarenee@amazon.com.
  
  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.
  
  We're dedicated to supporting new team members. Our team has a broad mix of experience levels and Amazon tenures, and we’re building an environment that celebrates knowledge sharing and mentorship.
  
  Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.
  
  

BASIC QUALIFICATIONS

• BS in computer science, or related technical, math, or scientific field
• 1+ years of relevant experience in building large scale enterprise IT systems
• 1+ year of experience with data engineering, ETL, and data wrangling
• Current, active US Government Security Clearance of TS/SCI with Polygraph
  
  

PREFERRED QUALIFICATIONS

• Masters 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
• 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
• 1+ year of public cloud computing experience in AWS