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Aws Machine Learning Jobs in Silver Spring, MD (NOW HIRING)

Samprasoft

Machine Learning Engineer

Mclean, VA · On-site

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

Ai Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

Full Scope

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly ... Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.

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How much do aws machine learning jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for aws machine learning in Silver Spring, MD is $72.43, according to ZipRecruiter salary data. Most workers in this role earn between $64.38 and $84.47 per hour, depending on experience, location, and employer.

What is an AWS Machine Learning job?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

What are the key skills and qualifications needed to thrive in the Aws Machine Learning position, and why are they important?

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

What are some typical responsibilities for someone working in an AWS Machine Learning role?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.
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Aws Machine Learning jobs near you
Machine Learning Engineer

Machine Learning Engineer

Samprasoft

Mclean, VA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

GCP/AWS Machine Learning Engineer

Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for taking on new initiatives to design, build, and deploy machine learning models in a client solution-oriented environment. As a member of our team, you will make an immediate impact on building and expanding current technology platforms across AWS and GCP.

What you will do:

  • Work within an agile team that includes members with cross-functional skills
  • Collaborate closely with other functional teams to design, build, test, and deploy AI solutions to address market needs
  • Design and implement Machine Learning algorithms and models into software solutions for our enterprise customers by using common machine learning frameworks, including establishing and training machine learning and deep learning models at scale for computer vision (image recognition, object detection, image generation), machine translation, language modeling, rankings and recommendations, speech recognition, etc.
  • Design, build, and implement cloud native applications using the GCP and AWS services, event streaming technologies, and various open source frameworks
  • Build distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time to feed machine learning algorithms
  • Incorporate real-time data streams to produce highly predictive features in our models
  • Write understandable, testable, and secure code with an eye towards quality and maintainability.

What we are looking for:

  • At least a Bachelor's degree in Computer Science, Mathematics, related technical field or equivalent practical experience.
  • A blend of data engineering, machine learning, and product innovation skills that let you jump into a fast-paced environment and contribute on day one
  • Familiar with monitoring, deployment tools, platforms and Infrastructure as Code (IaC)
  • At least 5 years of experience designing and implementing software solutions for complex problems
  • At least 3 years of experience with cloud computing platform (AWS and GCP)
  • At least 3 years of experience with Cloud Native Architecture, Docker, Microservices, Kubernetes, EKE/GKE, serverless computing, etc.
  • At least 3 years of experience as a data engineer, with large-scale data ecosystems including data lake, data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
  • Experience with building and deploying ML-based solutions and proficiency in common machine learning frameworks such as TensorFlow, XGBoost, scikit-learn, Pytorch and ONNX and programming languages (Python, Java, Go, etc.

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