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Training Ai Models Jobs in Virginia (NOW HIRING)

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 ...

Halvik

AI/ML Subject Matter Expert

Vienna, VA · On-site

$195K - $210K/yr

Experience building feature repositories for AI-ML model training * Project work in deep learning, transformers, computer vision, NLP, or chatbot development * Experience in developing Generative AI ...

Goldbelt, Inc.

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 ...

Halvik-

AI/ML Subject Matter Expert

Vienna, VA · On-site

$100 - $130/hr

Experience building feature repositories for AI-ML model training * Experience in developing Generative AI applications especially using LLMs in domains such as NLP and image processing * Knowledge ...

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 ...

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 ...

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Training Ai Models information

What is a training AI model?

A Training AI Models job involves developing, refining, and optimizing machine learning models by providing them with relevant data, adjusting parameters, and evaluating their performance. Professionals in this role clean and preprocess data, select appropriate algorithms, and fine-tune models for accuracy and efficiency. They may also work with engineers and researchers to ensure models generalize well to real-world applications. The goal is to create AI systems that perform specific tasks effectively, such as natural language processing, image recognition, or predictive analytics.

What are common challenges faced when training AI models, and how are they addressed?

One of the most common challenges in training AI models is handling large, complex datasets that often contain errors or inconsistencies, which can impact model performance. Professionals in this role frequently collaborate with data engineers and subject matter experts to clean and properly label data, as well as implement quality assurance checks throughout the process. Additionally, tuning model parameters and addressing issues such as overfitting or underfitting often require experimentation and iterative testing. Most teams employ version control and hold regular review sessions to ensure best practices are followed, making collaboration and communication essential parts of overcoming these challenges.

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

To thrive in Training AI Models, you need strong programming skills in languages like Python, a solid understanding of machine learning concepts, and typically a degree in computer science, data science, or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and familiarity with data preprocessing and annotation tools are commonly required; certifications in AI or data science can be advantageous. Effective communication, keen attention to detail, and collaboration are vital soft skills for working with cross-functional teams and ensuring data quality. These abilities are crucial for developing accurate models, delivering impactful AI solutions, and maintaining high standards throughout the model development lifecycle.

Can you get paid to train AI models?

Training AI models is a job that can be paid, especially for roles such as AI trainers, data annotators, or machine learning engineers. Compensation varies based on experience, location, and the complexity of the tasks, and often involves working with labeled datasets, coding, and understanding AI frameworks.

How to become a training AI models?

To become a training AI models professional, develop strong skills in programming languages like Python, understand machine learning algorithms, and gain experience with data preprocessing and model evaluation. Familiarity with frameworks such as TensorFlow or PyTorch and a background in computer science or data science are also important. Certifications or courses in AI and machine learning can enhance your qualifications.

What job trains AI models?

A job that trains AI models is typically called an AI/ML engineer or data scientist. These roles involve developing, testing, and refining machine learning algorithms using programming skills in languages like Python and tools such as TensorFlow or PyTorch. They often require knowledge of data preprocessing, model evaluation, and experience with large datasets.

What are the most commonly searched types of Training Ai Models jobs in Virginia?

The most popular types of Training Ai Models jobs in Virginia are:

What are popular job titles related to Training Ai Models jobs in Virginia?

For Training Ai Models jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Training Ai Models jobs in Virginia look for?

The top searched job categories for Training Ai Models jobs in Virginia are:

What cities in Virginia are hiring for Training Ai Models jobs?

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Training Ai Models jobs near you
Infographic showing various Training Ai Models job openings in Virginia as of August 2026, with employment types broken down into 55% Full Time, 19% Part Time, and 26% Contract. Highlights an 65% In-person, and 35% Remote job distribution.

AI Engineer - Mission Innovation Lab

Software Engineering Institute | Carnegie Mellon University

Arlington, VA • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
The Software Engineering Institute at Carnegie Mellon University is seeking an AI Engineer to conduct research in applied artificial intelligence and develop robust AI solutions for the defense and national security sectors. The role involves designing and deploying AI models and collaborating with interdisciplinary teams to operationalize AI technologies for mission capabilities.
Responsibilities:
• Design, develop, and fine‑tune a variety of AI models.
• Design autonomous agents and multi‑step pipelines using LangChain, ReAct, tool‑calling, or custom orchestration; employ the Model Context protocol to manage stateful interactions.
• Build Retrieval‑Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications.
• Implement end‑to‑end data pipelines, ETL processes, and back‑end services (Python, C/C++, Java) that feed data to models.
• Create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning; maintain model registries, monitoring, and version control of context protocols.
• Produce rapid prototypes, run benchmarks, and conduct robustness/adversarial testing in realistic environments.
• Work closely with senior ML engineers, software developers, and government customers; mentor junior staff and contribute to design reviews and documentation.
• Stay current with emerging LLM architectures, agentic paradigms, PEFT/LoRA methods, and AI‑safety techniques; translate new research into operational capabilities.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field with at least eight (8) years of relevant experience, or a MS degree in the same with at least five (5) years of relevant experience.
• You will be subject to a background investigation and must be able to obtain and maintain an active Department of War (DoW) security clearance.
• You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.
• Proficiency in Python and at least one compiled language (C/C++ or Java); experience with REST/GraphQL APIs and containerization.
• Strong grasp of ML theory (supervised, unsupervised, reinforcement learning) and evaluation metrics.
• Hands‑on experience fine‑tuning LLMs and using frameworks such as Hugging Face Transformers, LangChain, or comparable agent tools.
• Familiarity with building RAG pipelines (vector stores, dense/sparse retrievers).
• Experience applying PEFT/LoRA methods (e.g., LoRA, adapters) to large models.
• Understanding of Model Context protocols for managing model state across multi‑turn interactions.
• Experience building evaluation frameworks, benchmarks, or data quality pipelines.
• Experience with TensorFlow, PyTorch, or JAX; knowledge of data‑pipeline tools (Airflow, Prefect, Ray) is a plus.
• Awareness of DevSecOps practices (CI/CD, GitOps, container security scanning, model‑registry concepts) is desirable.
Preferred:
• Deploying LLM APIs (FastAPI, gRPC) at scale, handling latency and load balancing.
• Building multi‑tool agents, planner‑executor loops, or tool‑calling pipelines for complex decision‑making.
• Conducting adversarial testing, implementing input sanitization, and contributing to AI‑safety research.
• Utilizing GPU/TPU resources, mixed‑precision training, and distributed training frameworks such as DeepSpeed or ZeRO.
• Prior work on defense, intelligence, or government‑focused AI projects and familiarity with DoW acquisition or compliance processes.
• Contributing to open‑source AI and ML libraries, agentic frameworks, or context‑protocol implementations.
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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