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Ai Model Training Jobs in Virginia (NOW HIRING)

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 ...

... AI model accuracy. * Document experimental findings and processes with a focus on clarity for AI training data. * Collaborate with interdisciplinary teams to ensure scientific rigor and data ...

... AI model accuracy. * Document experimental findings and processes with a focus on clarity for AI training data. * Collaborate with interdisciplinary teams to ensure scientific rigor and data ...

... AI model accuracy. * Document experimental findings and processes with a focus on clarity for AI training data. * Collaborate with interdisciplinary teams to ensure scientific rigor and data ...

... AI model accuracy. * Document experimental findings and processes with a focus on clarity for AI training data. * Collaborate with interdisciplinary teams to ensure scientific rigor and data ...

Showing results 21-40

Ai Model Training information

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.

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

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

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

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

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

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

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

Cities in Virginia with the most Ai Model Training job openings:

Infographic showing various Ai Model Training job openings in Virginia as of August 2026, with employment types broken down into 76% Full Time, 10% Part Time, and 14% Contract. Highlights an 60% In-person, and 40% Remote job distribution.

Strategic Advisor, Nonprofit Research and Advanced AI, AWS Global Nonprofit Business

Amazon

Arlington, VA

$116K - $154K/yr

Full-time

Re-posted 7 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,154 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers


Job description

Amazon Web Services (AWS) Nonprofit Business (NPO) is seeking a research industry expert and strategic advisor with deep research background combined with expertise in advanced cloud services for research computing. This person will serve as an advisor and executive-level relationship builder across nonprofit research institutions and other similarly advanced customers with complex AI, model-building, and high-performance computing use cases-driving adoption of AWS's advanced compute, AI/ML, and HPC services for research workloads.
The focus of this role is on leveraging cloud and advanced AI services to accelerate research and advance mission impact.

The Strategic Advisor will operate across the NPO business as a shared strategic resource, building executive relationships at the C-suite, Chief Research Officer, and Principal Investigator level; influencing research computing policy (including NIH and NSF funding mechanisms); generating qualified pipeline across NPO Research territories and other similarly advanced accounts; and positioning AWS as the platform of choice for next-generation research computing.
This role builds the executive-level and industry-wide presence that opens doors, shapes market perception, and creates net-new demand across the portfolio. This position benefits all territories within the Nonprofit Research team as well as other NPO accounts with comparably advanced technical workloads, amplifying impact across the business.


Key job responsibilities
1. Strategic Advisory & Strategic Engagement
Build trusted relationships at the C-suite, Chief Research Officer, and Principal Investigator level across research institutions and other similarly advanced NPO customers with complex AI/ML and model-building use cases.
Conduct executive listening sessions and strategic workshops to expose organizational goals, current structures, blind spots, and drive alignment with measurable accountability
Maintain tool-agnostic credibility to access senior decision-makers; serve as a trusted, objective resource for executive leaders
Build and maintain a set of active, deep executive relationships across NPO Research territories and other advanced accounts
Design and facilitate executive engagement programs (cohorts, roundtables, advisory boards) spanning both research institutions and advanced AI/ML customers
2.

Advanced Cloud Services for Research & AI/ML
Position AWS compute, storage, AI/ML, and HPC services as the platform for next-generation research computing - genomics pipelines, climate modeling, computational biology, AI for scientific discovery.
Develop and maintain deep expertise across research computing domains and advanced AI/ML architectures: genomics, computational biology, climate modeling, AI/ML for science, research data platforms, and large-scale model training
Proactively identify industry trends and position AWS to anticipate customer needs (e.g., AI for research, data platforms for climate science, high-performance computing for genomics, foundation model fine-tuning)
Define and execute go-to-market strategy for nonprofit research institutes and advanced AI/ML customers aligned with AWS business plans and priorities
Serve as the specialist advisory resource when NPO accounts require deep technical industry-specific credibility for complex AI, model-building, or HPC workloads
3. Thought Leadership & Industry Presence
Deliver presentations at research events and industry conferences; contribute to advisory boards; publish through industry-appropriate channels (academic conferences, research publications, professional forums, LinkedIn)
Maintain credibility within the research community and among advanced AI/ML practitioners through continued scholarly and technical engagement
Contribute to research advisory board presence and seek committee participation that provides direct influence over research computing and AI adoption
Present to leadership, mapping research industry insights and emerging AI/ML trends and applications in the nonprofit sector to business value
4

Pipeline Development & Business Growth
Generate qualified pipeline across NPO Research territories and other similarly advanced accounts through proactive business development
Identify and develop new workload opportunities in pipeline - including AI/ML model training, HPC migration, and cloud-native research data platforms
5. Policy & Funding Ecosystem
Cultivate relationships with NIH, NSF, and other federal research funding organizations
Advocate for cloud computing in research funding mechanisms; initiate and influence active policy discussions
Evaluate existing grants and proactively engage PIs to offer assistance with cloud-based solution designs
6. Cross-Functional Collaboration
Partner closely with Account Managers across all territories via joint account planning; coordinate with SAs to convert strategic pipeline into revenue
Work with partnership, program, and marketing teams to create and execute strategic account plans
Aggregate insights from executive engagements to inform new solutions, sales motions, and campaigns
Serve as a bridge between Research territories, SA team, and other NPO teams, ensuring advanced AI/ML expertise is accessible across the organization.
A day in the life
Your morning starts with a Chief Research Officer listening session at a biomedical research institute exploring HPC migration

Midday, you join an account planning call with an Account Manager and SA to advance a genomics pipeline opportunity. After lunch, you deliver a keynote at a virtual research computing symposium, then prep a workshop for a climate nonprofit scaling AI-driven modeling on GPU clusters. You close the day reviewing an NSF funding mechanism and advising a PI on a cloud-native grant proposal - opening doors that drive pipeline across NPO.
About the team
The AWS Nonprofit Business team helps nonprofit organizations harness cloud to advance their missions - from modernizing constituent engagement to deploying AI-powered solutions that amplify impact

Within this team, Nonprofit Research supports premier research institutions across biomedical, climate, policy, and applied sciences. These organizations face significant barriers: uncertain funding, evolving compliance, multidisciplinary demands, and talent retention challenges. AWS helps overcome them with high-performance computing, scalable storage, secure collaboration, and AI/ML tools - enabling researchers to focus on discovery rather than infrastructure.
Diverse Experiences
AWS values diverse experiences

Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform.

We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams

Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony

Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US