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Aws Machine Learning Engineer Jobs in Virginia (NOW HIRING)

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

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 ...

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 ...

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 ...

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 ...

Machine Learning Engineer

Ashburn, VA · On-site

$110 - $170/hr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related ...

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Machine Learning Engineer General Information Requisition #728 Locations USA-VA-Chantilly Posting ... AWS Cloud experience * Experience with Graph Analysis * Security Plus Clearance Requirements:

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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 Aug 21, 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 is an AWS machine learning engineer?

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 are the key skills and qualifications needed to thrive as an AWS machine learning engineer?

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 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.

Infographic showing various Aws Machine Learning Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,665 per year, or $61.4 per hour.

Machine Learning Engineer

Cymertek Corporation

Reston, VA • On-site

Full-time

Re-posted 16 days ago


Job description

Job Summary:
Cymertek Corporation is seeking a talented and innovative Machine Learning Engineer to join their team and help build intelligent systems that drive impactful business solutions. The role involves designing, developing, and deploying machine learning models to solve complex problems and improve decision-making processes, while collaborating with data scientists and engineers.
Responsibilities:
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
Qualifications:
Required:
• TS/SCI Full Poly (Please note this position requires full U.S. Citizenship)
• Bachelor's Degree
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
• Proficiency in programming languages (e.g., Python, R, Java)
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Expertise in model evaluation techniques and metrics
• Strong knowledge of version control tools (e.g., Git)
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
• Understanding of database technologies (e.g., SQL, NoSQL)
Preferred:
• Experience with natural language processing (NLP)
• Knowledge of deep learning techniques (e.g., CNNs, RNNs)
• Familiarity with deployment tools (e.g., Docker, Kubernetes)
• Experience with data augmentation and synthetic data generation
• Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
• Knowledge of edge computing and model optimization for deployment
Company:
With headquarters in Maryland, Cymertek [/'sī-mer-tek/] Corporation provides superior consulting services for the implementation of high quality information systems. Founded in 2010, the company is headquartered in Laurel, USA, with a team of 11-50 employees. The company is currently Early Stage.