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Aws Machine Learning Engineer Jobs in Virginia (NOW HIRING)

Full Scope

Machine Learning Engineer

Reston, VA

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.

Steampunk

Machine Learning Engineer

Mclean, VA

$115K - $150K/yr

We are looking for seasoned Machine Learning Engineer to work with our existing team of Data ... Knowledge of cloud platforms such as AWS, Google Cloud, or Azure. * Experience with version control ...

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 ...

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 ...

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

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

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 ...

Steampunk

Machine Learning Engineer

Mclean, VA

$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 ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Chantilly, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Tysons, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

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Aws Machine Learning Engineer information

See Virginia salary details

$31.2K

$127.7K

$191.8K

How much do aws machine learning engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for aws machine learning engineer in Virginia is $127,665.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AWS Machine Learning Engineer, and why are they important?

To thrive as an AWS Machine Learning Engineer, you need strong proficiency in machine learning algorithms, programming languages like Python, and a solid understanding of cloud architecture, typically supported by a degree in computer science or a related field. Familiarity with AWS services such as SageMaker, Lambda, and S3, as well as relevant certifications like AWS Certified Machine Learning – Specialty, is highly valuable. Strong problem-solving, collaboration, and communication skills set top performers apart in this role. These skills ensure successful design, deployment, and optimization of scalable machine learning solutions on AWS that meet business needs.

How does an AWS Machine Learning Engineer typically collaborate with data scientists and DevOps teams?

As an AWS Machine Learning Engineer, you’ll work closely with data scientists to operationalize models, ensuring they are scalable and production-ready on AWS platforms. You’ll also frequently collaborate with DevOps teams to automate deployment pipelines, monitor model performance, and manage infrastructure using AWS services like SageMaker, Lambda, and CloudFormation. This cross-functional teamwork is essential for maintaining reliable, efficient ML workflows and for quickly resolving issues that arise in live environments.

What are AWS Machine Learning Engineers?

AWS Machine Learning Engineers are specialized professionals who design, build, deploy, and manage machine learning models using Amazon Web Services (AWS) cloud infrastructure. They leverage AWS tools and services, such as SageMaker, to create scalable and efficient machine learning solutions for businesses. Their responsibilities include data preparation, model training, optimization, deployment, and monitoring in a cloud environment. AWS Machine Learning Engineers often collaborate with data scientists, software engineers, and DevOps teams to integrate machine learning models into production systems.

What is the difference between Aws Machine Learning Engineer vs Data Scientist?

AspectAws Machine Learning EngineerData Scientist
CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, deployment pipelinesData analysis, modeling, research environments
Industry UsageTech, finance, healthcare using AWS for ML solutionsResearch, analytics, business intelligence
Search/Comparison IntentFocus on cloud-based ML deployment and engineeringFocus on data analysis and modeling

While both roles involve working with data and machine learning, Aws Machine Learning Engineers specialize in deploying ML models on AWS cloud platforms, focusing on infrastructure and scalable solutions. Data Scientists primarily analyze data, build models, and generate insights, often using a variety of tools and programming languages. The roles overlap in skills but differ in their primary focus and work environment.

What are popular job titles related to Aws Machine Learning Engineer jobs in Virginia? For Aws Machine Learning Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Aws Machine Learning Engineer jobs in Virginia look for? The top searched job categories for Aws Machine Learning Engineer jobs in Virginia are:
Aws Machine Learning Engineer jobs near you
Infographic showing various Aws Machine Learning Engineer job openings in Virginia as of May 2026, with employment types broken down into 72% Full Time, 22% Part Time, and 6% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $127,665 per year, or $61.4 per hour.

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 13 days ago

Job description

Job Title:Machine Learning Engineer
Location:Fort Meade, MD
Required Clearance: TS/SCI w/ Full-Scope Poly
Salary:Competitive
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.
Key Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications:
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.

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