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Ai Model Training Jobs in Silver Spring, MD (NOW HIRING)

Doist

Senior AI/ML Engineer

Arlington, VA · On-site

$140 - $210/hr

Architect automated pipelines for model training, validation, testing, deployment, and monitoring * Develop reusable frameworks, libraries, and shared components that accelerate AI/ML delivery

540

Senior AI/ML Engineer

Arlington, VA · On-site

$120K - $165K/yr

Architect automated pipelines for model training, validation, testing, deployment, and monitoring * Develop reusable frameworks, libraries, and shared components that accelerate AI/ML delivery

540

Senior AI/ML Engineer

Arlington, VA · On-site

$120K - $165K/yr

Architect automated pipelines for model training, validation, testing, deployment, and monitoring * Develop reusable frameworks, libraries, and shared components that accelerate AI/ML delivery

Phase2 Technology

AI/ML Engineer

Fort George G Meade, MD · On-site

$99 - $225/hr

Experience developing and maintaining AI and ML pipelines for model training, validation, and deployment * Experience integrating AI and ML capabilities into production systems and mission workflows

Unissant

Senior AI Systems Architect

Ashburn, VA · On-site

$145K - $208K/yr

... model training, inference, monitoring, retraining, and operational management.Implement secure Gen-AI guardrails addressing:Hallucination mitigationPrompt injection preventionPrompt leakage ...

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All JobsAi Model Training JobsAi Model Training Jobs in Silver Spring, MD

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How much do ai model training jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for ai model training in Silver Spring, MD is $32.43, according to ZipRecruiter salary data. Most workers in this role earn between $19.62 and $40.53 per hour, depending on experience, location, and employer.

What is an AI model training?

An AI Model Training job involves preparing, training, and optimizing machine learning models using data. Professionals in this role preprocess datasets, select appropriate algorithms, adjust model parameters, and evaluate performance to improve accuracy. They work with frameworks like TensorFlow or PyTorch and may fine-tune models for specific tasks such as image recognition or natural language processing. This job requires expertise in data science, programming, and statistical analysis to ensure models perform efficiently in real-world applications.

What are the typical work responsibilities of someone in AI model training?

Professionals in AI Model Training are typically responsible for collecting, preparing, and processing large datasets, designing and implementing machine learning models, and evaluating their performance using statistical methods. You may work closely with data engineers, software developers, and product managers to ensure models meet business objectives and integrate smoothly into existing systems. Regular responsibilities also include tuning hyperparameters, troubleshooting model issues, and staying up-to-date with the latest advancements in AI. This role often involves a mix of independent technical work and collaborative problem-solving sessions with the broader team.

What are the key skills and qualifications needed to thrive in the AI model training position, and why are they important?

To excel in AI Model Training, you need a strong background in machine learning, programming (especially Python), data analysis, and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and certifications in AI or data science are highly advantageous. Strong problem-solving skills, attention to detail, and the ability to communicate complex ideas effectively make candidates stand out. These competencies are crucial for developing accurate, efficient AI models and collaborating seamlessly within multidisciplinary teams.

Are there any legit AI model training jobs?

Yes, legitimate AI model training jobs are available in the tech industry, often requiring skills in machine learning, programming (such as Python), and data annotation. These roles can be found at technology companies, research institutions, and through reputable job boards, and may involve tasks like data labeling, model tuning, and algorithm development.

Can you get paid to train AI models?

Yes, AI model training is a paid role that involves developing and fine-tuning machine learning algorithms, often requiring skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch. Salaries vary based on experience, location, and the complexity of the models being trained.

How do I become an AI model trainer?

To become an AI model trainer, you typically need a strong background in computer science, machine learning, or data science, often with a bachelor's or master's degree. Skills in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and understanding of data preprocessing are essential. Gaining hands-on experience through projects or internships can also improve your prospects in this role.

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Ai Model Training jobs near you
Infographic showing various Ai Model Training job openings in Silver Spring, MD as of August 2026, with employment types broken down into 60% Full Time, 26% Part Time, and 14% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $67,450 per year, or $32.4 per hour.

Senior AI/ML Engineer

Doist

Arlington, VA • On-site

$140 - $210/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

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

Job description

540 is seeking a Senior AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will lead the design and evolution of production AI/ML services and infrastructure that enable teams to develop, deploy, monitor, and scale models supporting complex defense missions. Working with software engineers, data engineers, data scientists, cybersecurity teams, and mission stakeholders, you will translate complex requirements into secure, scalable AI/ML solutions. You will define MLOps standards, guide technical delivery, and establish reusable capabilities supporting the end-to-end machine learning lifecycle.

Location : Arlington, VA Citizenship & Clearance Requirement : Per client requirements, candidates must be U.S. Citizens with an active DoW Secret (or higher) clearance Education Requirement: Bachelor’s degree in Computer Science, Engineering, or a related technical field preferred; equivalent combinations of education and relevant experience will be considered 540 Internal Thrive Level: Senior Software Engineer

WHY 540?

540 is a forward-thinking company that the government turns to in order to #getshitdone. We don't just talk about innovation - we deliver it. We break down barriers, build impactful technology, and solve mission-critical problems.

HOW YOU'LL DRIVE IMPACT
  • Lead the architecture and evolution of AI/ML services, platforms, and lifecycle capabilities supporting WDP
  • Translate mission requirements into scalable AI/ML architectures and implementation strategies
  • Define MLOps standards, reusable patterns, and best practices across engineering teams
  • Architect automated pipelines for model training, validation, testing, deployment, and monitoring
  • Develop reusable frameworks, libraries, and shared components that accelerate AI/ML delivery
  • Design model-serving platforms supporting secure, scalable, and reliable batch or real-time inference
  • Establish model monitoring, performance tracking, drift detection, explainability, and governance capabilities
  • Define practices for model versioning, artifact management, reproducibility, feature engineering, and data lineage
  • Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost efficiency
  • Establish CI/CD, infrastructure-as-code, automated testing, and operational practices for AI/ML systems
  • Lead technical reviews and resolve complex issues spanning models, applications, data, infrastructure, and production services
  • Partner with cybersecurity teams to incorporate security, access control, auditing, and governance requirements
  • Communicate architecture decisions and mentor engineers and data scientists on AI/ML engineering and MLOps practices
REQUIRED SKILLS & EXPERIENCE
  • 9+ years of relevant AI/ML engineering, software engineering, or data science experience
  • Experience leading the design and delivery of enterprise-scale, production-grade AI/ML systems
  • Advanced software engineering experience using Python and commonly used AI/ML frameworks
  • Experience architecting automated model training, validation, deployment, and monitoring pipelines
  • Experience defining MLOps architecture, standards, and practices across engineering teams
  • Experience designing model-serving capabilities for batch and real-time inference
  • Experience deploying and operating models in cloud-based or containerized environments
  • Strong understanding of model evaluation, monitoring, drift detection, explainability, reproducibility, and governance
  • Experience with Docker, Kubernetes, or similar containerization and orchestration technologies
  • Experience establishing CI/CD, infrastructure-as-code, automated testing, and source-control practices
  • Experience architecting AI/ML solutions within AWS, Azure, or Google Cloud
  • Experience with data pipelines, distributed data processing, feature engineering, and data versioning
  • Ability to evaluate technical approaches and clearly communicate architecture decisions, risks, and tradeoffs
  • Experience leading technical reviews, mentoring engineers, and influencing technical direction
  • Ability to troubleshoot complex issues across applications, infrastructure, data, and machine learning systems
NICE TO HAVE
  • Experience leading AI/ML initiatives within DoW, federal, Advana, or other enterprise data environments
  • Experience architecting solutions using AWS SageMaker or comparable cloud AI/ML platforms
  • Experience with MLflow, Kubeflow, Airflow, Argo Workflows, Ray, Feast, or similar technologies
  • Experience building AI/ML platforms in secure, regulated, classified, or mission-critical environments
  • Experience with large language models, generative AI, retrieval-augmented generation, or foundation-model operations
  • Experience establishing responsible AI, model-risk-management, or AI-governance practices
  • Experience leading AI/ML platform modernization, technology evaluations, or proofs of concept
  • Currently holds, or is willing to obtain within 30 days of employment, an approved certification such as CCSP, CFR, FITSP-M, GSEC, Security+, or SSCP
BENEFITS & PERKS
  • Flexible PTO + all Federal holidays off
  • Health, dental and vision insurance plans
  • Flexible Spending Account (FSA)
  • 401k with employer match
  • Company-sponsored life insurance, short- and long-term disability
  • Professional development (training, certifications, conferences)
  • Paid cloud developer accounts
  • Referral bonuses
  • HQ office perks (parking / metro reimbursement, nitro coffee & lunches)
  • Annual social events (540 Week, hackathon, charity golf tournament, etc.)
  • Access to 540's Washington Capitals & Nationals tickets
EQUAL EMPLOYMENT OPPORTUNITY (EEO)

540's policy is to provide equal employment opportunity to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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