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Ai Model Training Jobs in Springfield, VA (NOW HIRING)

DCCA

SME - Data Engineer

Bethesda, MD · On-site

$122K - $146K/yr

They are seeking a Senior Data Engineer to design and implement large-scale data systems and prepare datasets for AI model training. Responsibilities : • Experience in designing and implementing ...

DCCA

SME - Data Engineer

Bethesda, MD · On-site

$122K - $146K/yr

The SME - Data Engineer will be responsible for designing and implementing large-scale data systems to support organizational data needs and creating datasets for AI model training. Responsibilities ...

Goldbelt, Inc.

AI/ML SME

Arlington, VA

$190K - $235K/yr

Document model assumptions, data inputs, and training parameters for reproducibility. * Conduct ... Prepare AI business case summaries that explain model purposes, value proposition, expected ...

New

Cp Marine Llc

AI/ML SME

Arlington, VA · On-site

$190K - $235K/yr

Document model assumptions, data inputs, and training parameters for reproducibility. * Conduct ... Prepare AI business case summaries that explain model purposes, value proposition, expected ...

Diaconia LLC

AI/ML SME

Springfield, VA · On-site

$130K - $160K/yr

The role will support development, enhancement, training, validation, deployment, and maintenance of AI/ML models, with emphasis on entity extraction, relationship identification, unstructured data ...

Booz Allen Hamilton

AI Integration Engineer

Mclean, VA · On-site

$105K - $141K/yr

Experience with AI/ML frameworks for model training and deployment such as PyTorch, TensorFlow, or Hugging Face Transformers * Experience implementingobservability and monitoring systemssuch as ...

Mindlance

AI Engineer

Washington, DC · On-site

$110K - $151K/yr

Develop code, deploy AI models and into production environments, and conduct ongoing model training * Monitor performance and troubleshoot issues and engage in fine-tuning the solutions to improve ...

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All JobsAi Model Training JobsAi Model Training Jobs in Springfield, VA

Ai Model Training information

See Springfield, VA salary details

$10

$32

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How much do ai model training jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for ai model training in Springfield, VA is $32.76, according to ZipRecruiter salary data. Most workers in this role earn between $19.86 and $40.91 per hour, depending on experience, location, and employer.

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.

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 is an AI Model Training job?

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 job categories do people searching Ai Model Training jobs in Springfield, VA look for? The top searched job categories for Ai Model Training jobs in Springfield, VA are:
What cities near Springfield, VA are hiring for Ai Model Training jobs? Cities near Springfield, VA with the most Ai Model Training job openings:
Ai Model Training jobs near you
Infographic showing various Ai Model Training job openings in Springfield, VA as of July 2026, with employment types broken down into 82% Full Time, 11% Part Time, 3% Temporary, and 4% Contract. Highlights an 73% In-person, and 27% Remote job distribution, with an average salary of $68,151 per year, or $32.8 per hour.
Product Manager, AI/ML & Foundation Models (R4991)

Product Manager, AI/ML & Foundation Models (R4991)

Shield AI

Washington, DC

Full-time

Posted 10 days ago

Job description

Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:
 
The Product Manager will drive the strategy and execution of Shield AI's next-generation autonomy intelligence stack-enabling customers and internal teams to train, evaluate, and deploy foundation and domain models that power resilient autonomy at the edge. This PM owns the product vision and roadmap for the Hivemind AI Platform (Forge, training pipelines, data infrastructure, evaluation, and deployment toolchains), ensuring we can manufacture, govern, and field advanced world models, robotics foundation models, and vision-language-action systems safely and at scale. 
 
This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning-capabilities that are central to Shield AI's strategic direction. 
 
This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.
What you'll do:
  • AI Model Development & Training Platform
  • Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines.
  • Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization.
  • Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.
  • Data, Simulation & Synthetic Data Factory
  • Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation.
  • Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.
  • Safe Deployment & Model Governance
  • Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence.
  • Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments.
  • Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.
  • Edge Deployment & AI Factory Integration
  • Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors.
  • Define requirements for distillation, quantization, and inference tooling as part of the "three-computer" development and deployment model.
  • Ensure closed-loop workflows between cloud model training and edge-native execution.
  • Cross-Functional Leadership
  • Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints.
  • Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories.
  • Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.
  • User & Customer Impact
  • Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform.
  • Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements.
  • Lead demos and onboarding for model-development capabilities across internal and external teams.
Required qualifications:
  • 7+ years of experience in product management or highly technical ML/AI product roles.
  • 2+ years of experience in a hands-on software development role.
  • Strong engineering background (Computer Science, Electrical Engineering, Robotics, or related field).
  • Deep understanding of foundation models, robotics models, multimodal models, MLOps, and training infrastructure.
  • Experience managing complex products spanning data pipelines, cloud training clusters, model governance, and edge deployments.
  • Proven success partnering with research teams to transition ML innovations into stable, production-grade workflows.
  • Familiarity with simulation-based data generation and large-scale data management.
  • Excellent communicator with strong cross-functional leadership skills.
Preferred qualifications:
  • Experience working on autonomy, robotics, embedded AI, or mission-critical systems.
  • Hands-on familiarity with GPU infrastructure, distributed training, or data lakehouse architectures.
  • Experience supporting defense, dual-use, or safety-critical AI systems.
  • Background designing or operating AI Factory-style pipelines (data training evaluation distillation edge deployment).
  • Advanced degree in engineering, ML/AI, robotics, or a related field.
$190,000 - $290,000 a year
#LI-DM2
#LE

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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