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Face Modeling Jobs in Virginia (NOW HIRING)

Company Description Need local candidates or those candidates only who can go for Face to Face ... Should have good knowledge in data warehouse concepts and dimensional modeling * Should have good ...

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Software Engineer II

Herndon, VA · On-site

$100K - $137K/yr

Optimize model inference performance and deployment workflows. * Develop secure, scalable machine ... Strong proficiency with PyTorch and the Hugging Face ecosystem, including Transformers, PEFT ...

Software Engineer II

Herndon, VA · On-site

$100K - $137K/yr

Optimize model inference performance and deployment workflows. * Develop secure, scalable machine ... Strong proficiency with PyTorch and the Hugging Face ecosystem, including Transformers, PEFT ...

AI/ML Technical Lead

Fort Belvoir, VA · On-site

$90 - $120/hr

Evaluate model performance and improve accuracy, efficiency, reliability, and scalability ... Experience with tools such as LangChain, Hugging Face, OpenAI API, Azure AI, AWS SageMaker, or ...

Showing results 41-60

Face Modeling information

See Virginia salary details

$21

$39

$75

How much do face modeling jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for face modeling in Virginia is $39.99, according to ZipRecruiter salary data. Most workers in this role earn between $30.96 and $43.12 per hour, depending on experience, location, and employer.

How much do face models get paid?

Face models typically earn between $50 and $300 per hour, depending on factors such as experience, the type of project, and the usage rights. Rates can vary widely for commercial, editorial, or promotional work, with some projects paying a flat fee or licensing fees for specific uses.

How do you get into face modeling?

To become a face model, individuals typically build a portfolio with professional photographs highlighting their facial features, often work with modeling agencies or casting directors, and may need to meet specific criteria such as clear skin and symmetrical features. Developing good skin care, practicing facial expressions, and understanding industry standards can improve chances of success.

What is face modeling?

Face modeling is a specialized area within modeling and digital arts that focuses on representing facial features for various purposes such as fashion, advertising, animation, video games, or 3D graphics. In the context of fashion and beauty, face models are hired for close-up shots showcasing products like cosmetics, jewelry, or skincare. In digital media, face modeling involves creating realistic or stylized digital representations of human faces using 3D modeling software. The skills required can vary from having the right facial features and expressions for photography to technical expertise in digital modeling.

What are the requirements for a face model?

Face modeling requires clear, symmetrical facial features, good skin condition, and a neutral or expressive look suitable for photography or casting. Some roles may require specific skin tones or features, and models often need to be comfortable with photoshoots and following directions. A portfolio or headshots are typically necessary to showcase your appearance to clients or agencies.

What is the difference between Face Modeling vs Makeup Artist?

AspectFace ModelingMakeup Artist
Required CredentialsPortfolio, modeling experience, sometimes certificationsCosmetology license, makeup certifications
Work EnvironmentPhoto shoots, fashion shows, commercialsSalons, studios, events, photoshoots
Industry UsageFashion, advertising, entertainmentBeauty, fashion, entertainment

Face Modeling involves showcasing facial features for brands, photographers, and designers, focusing on appearance and expressions. Makeup Artists apply cosmetics to enhance or transform faces for various occasions. While both roles work closely with facial aesthetics, Face Modeling emphasizes natural or styled looks for visual media, whereas Makeup Artists create specific looks through makeup application. Understanding these differences helps clients choose the right professional for their needs.

What are the key skills and qualifications needed to thrive as a face model, and why are they important?

To thrive as a Face Model, you need distinct facial features, clear skin, and a professional attitude, often supported by a strong portfolio and agency representation. Familiarity with posing techniques, makeup application, and industry standards is essential, as is experience working with cameras and lighting setups. Confidence, adaptability, and strong interpersonal skills help models collaborate effectively with photographers, stylists, and clients. These skills and qualities are crucial for consistently meeting client expectations and succeeding in a competitive, image-focused industry.

What are some common challenges faced by professionals in face modeling, and how can they be addressed?

Face modeling often requires adapting to different makeup styles, lighting conditions, and camera angles, which can be challenging for both new and experienced models. Maintaining healthy skin and facial expressions is essential, as the face is the primary focus in this role. Additionally, face models frequently work closely with photographers, makeup artists, and creative directors, so effective communication and flexibility are key. Staying updated on industry trends and building a strong, diverse portfolio can also help overcome these challenges and open up more opportunities.
What are popular job titles related to Face Modeling jobs in Virginia? For Face Modeling jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Face Modeling jobs in Virginia look for? The top searched job categories for Face Modeling jobs in Virginia are:
What cities in Virginia are hiring for Face Modeling jobs? Cities in Virginia with the most Face Modeling job openings:
Infographic showing various Face Modeling job openings in Virginia as of July 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $83,176 per year, or $40 per hour.

Senior Manager, Data Science - Model Risk Office

Capital One

Mclean, VA • On-site

Full-time

Re-posted 27 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

93rd of 170 rated banks


Job description

Senior Manager, Data Science - Model Risk Office
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
The Capital One Model Risk Office is dedicated to safeguarding the company from model failures while simultaneously enhancing decision-making through models, including unique risks associated with Generative AI (GenAI). Leveraging expertise in statistics, software engineering, and business, we strive to achieve optimal results for both Risk Management and the broader Enterprise. We prioritize long-term success by continually investing in future capabilities: acquiring new skills, developing superior tools, and cultivating strong relationships with trusted partners. Our approach involves learning from past errors to develop increasingly robust techniques that prevent recurrence.
Role Description
In this role, you will:
  • Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
  • Leverage a broad stack of technologies - from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more - to reveal the insights hidden within huge volumes of multi-modal data
  • Build machine learning models to challenge "champion models" that are deployed in production today and contribute to the model governance framework for the next generation of models
  • Validate a wide variety of models across multiple business domains within our Enterprise Services division, and flex your interpersonal skills to present how identified model risks could impact the business to executives.

The Ideal Candidate is:
  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
  • Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
  • A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:
  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics
    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
  • At least 2 years of experience leveraging open source programming languages for large scale data analysis
  • At least 2 years of experience working with machine learning
  • At least 2 years of experience utilizing relational databases

Preferred Qualifications:
  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 1 year of experience managing people
  • At least 5 years' experience in Python, Scala, or R for large scale data analysis
  • At least 5 years' experience with machine learning

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Chicago, IL: $209,000 - $238,500 for Sr Mgr, Data Science
McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science
Richmond, VA: $209,000 - $238,500 for Sr Mgr, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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