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

Dark Wolf

Machine Learning Engineer

Chantilly, VA · On-site

... g., AWS, Azure, GCP) and their machine learning services. • Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines. • Strong analytical and problem ...

Steampunk

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with ... Knowledge of cloud platforms such as AWS, Google Cloud, or Azure. * Experience with version control ...

Steampunk

Machine Learning Engineer

Mclean, VA · On-site

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with ... Knowledge of cloud platforms such as AWS, Google Cloud, or Azure. * Experience with version control ...

Geico

Machine Learning Engineer II

Bethesda, MD · On-site

Expertisein cloud platforms (AWS, Azure, GCP) and containerization technologies such as Docker, as well as orchestration tools like Kubernetes. * Proven experience in deploying machine learning ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure, including ...

New

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site +1

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Experience with cloud platform (AWS, Azure and GCP), AWS experience preferred * Proven experience ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure, including ...

New

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Experience with cloud platform (AWS, Azure and GCP), AWS experience preferred * Proven experience ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Experience with cloud platform (AWS, Azure and GCP), AWS experience preferred * Proven experience ...

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Experience with cloud platform (AWS, Azure and GCP), AWS experience preferred * Proven experience ...

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How much do aws machine learning jobs pay per hour?

As of Jun 5, 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

Dark Wolf

Chantilly, VA • On-site

Full-time

Posted 21 days ago

Job description

Job Summary:
Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. They are seeking a highly motivated Machine Learning Engineer to design, develop, and implement machine learning models and algorithms to solve business problems.
Responsibilities:
• Design, develop, and implement machine learning models and algorithms to solve specific business problems.
• Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
• Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
• Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
• Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
• Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
• Troubleshoot and resolve issues related to machine learning models and pipelines.
• Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
• Contribute to the development of best practices and standards for machine learning development and deployment within the team.
• Document machine learning models, experiments, and deployment processes.
• Potentially work with large datasets and big data technologies.
• Optimize machine learning models for performance and efficiency.
Qualifications:
Required:
• Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
• Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
• Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
• Solid understanding of machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction, deep learning architectures).
• Experience with data preprocessing, feature engineering, and data visualization techniques.
• Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
• Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
• Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
• Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.
Preferred:
• Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
• Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
• Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience with building and deploying RESTful APIs.
• Familiarity with big data technologies and distributed computing.
• Experience with statistical modeling and inference.
Company:
Dark Wolf provides DevSecOps agile software development, information operations, penetration testing and incident response, applied research and rapid prototyping, machine learning, and mission support and engineering services to the Intelligence Community, national security, and Fortune 500 customers. Founded in 2009, the company is headquartered in Herndon, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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