Senior IoT Machine Learning Engineer, Public Sector - AWS Professional Services

Amazon Web Services
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Job Description

Are you excited by the development of solutions incorporating Edge devices, the Internet of Things (IoT), Machine Learning (ML) models, and cloud computing? Want to help the largest public sector customers and global enterprises derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from many different enterprises’ use cases of AWS Edge, IoT, and ML? Do you have a strong combination of deep technical knowledge, business acumen, and interpersonal skills?

At Amazon Web Services (AWS), we are helping large enterprises build Edge/IoT ML solutions on the AWS Cloud. We are applying ML techniques to large volumes of IoT and customer data against a wide spectrum of problems. Our Professional Services organization works together with our AWS customers to address their business needs using AI.

This position requires that the candidate selected be a U.S. citizen and obtain and maintain an active TS/SCI security clearance.

AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and being trusted advisers to our customers. If you have experience with IoT, Edge devices, and AI, and want to work with AWS sales, business development, solution architects, and service teams to drive AWS adoption, 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.

A successful candidate will be a person who enjoys diving deep into customer problems, doing analysis, discovering root causes, and designing long-term solutions. The candidate will be a person who likes to have fun, loves to learn, and wants to innovate in the world of Cloud/Edge hybrid deployments, IoT, and AI.

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.


  • Understand the customer’s business need and guide them to a solution using AWS services, platforms, and frameworks
  • Assist customers by being able to deliver an Edge/IoT ML project from beginning to end, including understanding the business need, eliciting requirements, and deploying solutions that deliver business impact to the organization
  • Use ML tools, such as Amazon SageMaker GroundTruth, Studio, Edge Manager, and Neo
  • Deploy to AWS Edge devices, including AWS Snowball Edge, Snowcone, and others
  • Use IoT tools, such as AWS IoT Core, Greengrass, and Events
  • Work closely with account teams, research scientist teams, and product engineering teams to drive implementation
  • Incorporate DevOps best practices to help our customers operationalize solutions after they are built

**If you have questions, wish to apply or refer someone contact Josh May directly -**


  • This position requires that the candidate selected be a U.S. citizen and obtain and maintain an active TS/SCI security clearance.
  • Bachelor’s or Master’s degree in computer science, or related technical, math, or scientific field
  • 8+ years of relevant experience in building large scale enterprise IT systems
  • 5+ years of experience with solution development using cloud technologies
  • 3+ years of experience with ML fields, e.g., natural language processing, computer vision, predictive maintenance
  • 3+ years of experience in one or more specific Edge / IoT / embedded / M2M industry (e.g., home automation, business automation, health, asset tracking, smart utilities, etc.)
  • Experience deploying ML models using AWS Sagemaker or similar cloud services
  • Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility
  • Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations


  • Master’s or PhD degree in computer science, or related technical, math, or scientific field
  • Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within our customers’ organizations
  • Experience compiling and deploying ML models to small-form-factor hardware, e.g., NVIDIA Jetson Xavier, particularly using AWS SageMaker Neo
  • Prior experience developing solutions for public sector
  • Experience developing cloud/edge hybrid solutions
  • Experience with embedded or real-time operating systems, and/or driver/kernel development
  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

Company Info.

Amazon Web Services

Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon providing on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide a variety of basic abstract technical infrastructure and distributed computing building blocks and tools. One of these services is Amazon Elastic Compute Cloud (EC2).

  • Industry
    Information Technology
  • No. of Employees
  • Location
    410 Terry Ave N, Seattle, WA, USA
  • Website
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