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Apprentice Machine Learning Testing Jobs in Manassas, VA

Venturegloballng

Engineer, Machine Learning

Arlington, VA · On-site

$157K - $185K/yr

Continuously push the practice forward, learning and testing newer and better ways of performing work. Qualifications Required experience * 5 years of machine learning engineering, software ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

Advise stakeholders on experimentation best practices and help design and implement A/B/n testing as needed. * Stay current with trends and developments in the AI, machine learning, and healthcare ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced ... Experience with adversarial evaluations, robustness testing, or AI safety. * Experience with ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment * Machine learning experience ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $200K/yr

Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment * Machine learning experience ...

Kitware

Machine Learning Engineer

Arlington, VA · On-site

$110K - $200K/yr

Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment * Machine learning experience ...

Koitecc Solutions

Machine Learning Engineer

Chantilly, VA · On-site

$120 - $180/hr

Machine Learning Engineer General Information Requisition #728 Locations USA-VA-Chantilly Posting ... testing and debugging tasks, deploying into target environments, setting up monitoring, and ...

Tekfortune Inc.

Machine Learning Engineer

Mclean, VA · On-site

$117K - $141K/yr

Machine Learning Engineer Hybrid in Mclean, VA Contract Must haves: - Python - AWS - Kubernetes ... Develop features, deploy applications, perform testing, and implement vulnerability fixes. * Debug ...

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How much do apprentice machine learning testing jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for apprentice machine learning testing in Manassas, VA is $19.36, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.15 per hour, depending on experience, location, and employer.

What does an apprentice machine learning testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What kinds of projects or tasks can I expect to work on as an apprentice machine learning testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What are the key skills and qualifications needed to thrive as an apprentice machine learning testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in Manassas, VA?

For Apprentice Machine Learning Testing jobs in Manassas, VA, the most frequently searched job titles are:

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The top searched job categories for Apprentice Machine Learning Testing jobs in Manassas, VA are:

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Cities near Manassas, VA with the most Apprentice Machine Learning Testing job openings:

Apprentice Machine Learning Testing jobs near you

Machine Learning / Federated-Learning Engineer

Mclean, VA • On-site

Steampunk
IT Services • 201 - 500 employees
Learn more about Steampunkexternal

Other

Posted 3 days ago

New

Job description

Overview
We are seeking a Machine Learning (ML) / Federated-Learning Engineer responsible for developing, implementing, and supporting machine learning solutions within controlled and distributed environments. This role will support the Bounded Use Case B demonstration through controlled model adaptation, fine-tuning, and federated learning workflows.
The ML / Federated-Learning Engineer will work across the machine learning lifecycle to develop and integrate model training and adaptation workflows, support distributed and federated learning capabilities, evaluate model performance, and ensure solutions operate within defined technical and security constraints. This role requires strong hands-on experience with machine learning engineering, model development, and distributed computing environments.
Contributions
  • Design, develop, and implement machine learning solutions supporting the Bounded Use Case B demonstration
  • Develop and execute controlled model adaptation and fine-tuning workflows based on defined use cases and requirements
  • Design, implement, and support federated learning workflows that enable distributed model training and adaptation
  • Develop and maintain machine learning pipelines supporting data preparation, model training, fine-tuning, evaluation, and deployment
  • Analyze and preprocess data, including feature engineering and transformation, to support machine learning workflows
  • Configure and optimize machine learning models and training processes to meet defined performance and operational requirements
  • Evaluate model performance, behavior, and effectiveness using established metrics and validation techniques
  • Develop processes and controls to ensure model adaptation and training occur within defined technical, security, and operational boundaries
  • Integrate machine learning capabilities with existing applications, platforms, data sources, and infrastructure
  • Troubleshoot model training, integration, performance, and distributed learning issues
  • Develop reusable code, tools, and automation to support machine learning and federated learning workflows
  • Collaborate with data scientists, software engineers, cloud engineers, cybersecurity teams, and other technical stakeholders to develop and integrate machine learning capabilities
  • Document machine learning architectures, workflows, configurations, testing results, and technical implementation decisions
  • Support version control, CI/CD, and other software engineering practices throughout the machine learning development lifecycle
  • Support an Agile software development lifecycle
  • Maintain awareness of emerging machine learning, model fine-tuning, federated learning, and distributed AI technologies and practices

Qualifications
Required:
  • Ability to obtain and maintain a government security clearance
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, or a related technical field, or equivalent relevant experience
  • 5+ years of experience in software engineering, data science, machine learning, AI engineering, or related technical disciplines, including hands-on machine learning engineering experience
  • Hands-on experience developing, training, fine-tuning, and evaluating machine learning models
  • Experience designing and implementing machine learning training and inference workflows
  • Experience with federated learning, distributed machine learning, or distributed model training concepts and architectures
  • Strong programming experience using Python and common machine learning libraries and frameworks
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies
  • Experience with data preprocessing, feature engineering, and model evaluation techniques
  • Experience developing and maintaining data and machine learning pipelines
  • Knowledge of model evaluation techniques, performance metrics, and validation methodologies
  • Experience integrating machine learning models and capabilities into applications or production environments
  • Understanding of distributed computing concepts and architectures
  • Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
  • Experience with version control systems such as Git and CI/CD practices
  • Experience troubleshooting machine learning model, pipeline, and integration issues
  • Strong analytical, problem-solving, communication, and collaboration skills

Preferred:
  • Hands-on experience implementing federated learning architectures or workflows
  • Experience with federated learning frameworks or technologies
  • Experience with large language models (LLMs), foundation models, or other generative AI technologies
  • Experience with parameter-efficient fine-tuning or other model adaptation techniques
  • Experience deploying and operating machine learning workloads in cloud environments
  • Knowledge of MLOps practices, model lifecycle management, and automated ML pipelines
  • Experience implementing machine learning solutions within controlled, secure, or restricted environments
  • Experience working within federal government or other highly regulated environments
  • Relevant cloud, machine learning, or AI certification

About steampunk
Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $115,000 to $150,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk's total compensation package for employees. Learn more about additional Steampunk benefits here.
Identity Statement
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. If you want to learn more about our story, visit http://www.steampunk.com.
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program.

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