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Face Modeling Jobs (NOW HIRING)

Hugging Face

Cloud ML DevRel Engineer - US remote

New York, NY · On-site +1

$61 - $81.50/hr

At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 ...

Hugging Face

Cloud ML DevRel Engineer - US remote

New York, NY · On-site +1

$61 - $81.50/hr

At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 ...

Sonsoft Inc

Data Modeling ,

Tampa, FL · On-site

$51.75 - $67/hr

Should be able to communicate by telephone, email or face to face. Travel may be required as per ... Modeling related tools Understanding of Data Modeling architectural principles Additional ...

Sonsoft Inc

Data Modeling ,

Livingston, NJ · On-site

$59.75 - $77.50/hr

Should be able to communicate by telephone, email or face to face. Travel may be required as per ... Modeling related tools Understanding of Data Modeling architectural principles Additional ...

Sonsoft Inc

Data Modeling ,

Warren, NJ

$56.75 - $73.75/hr

Should be able to communicate by telephone, email or face to face. Travel may be required as per ... Modeling related tools Understanding of Data Modeling architectural principles Additional ...

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How much do face modeling jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for face modeling in the United States is $40.33, according to ZipRecruiter salary data. Most workers in this role earn between $31.25 and $43.51 per hour, depending on experience, location, and employer.

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 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 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.

More about Face Modeling jobs
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What states have the most Face Modeling jobs? States with the most job openings for Face Modeling jobs include:
Face Modeling jobs near you
Cloud ML DevRel Engineer - US remote

Cloud ML DevRel Engineer - US remote

Hugging Face

New York, NY • Remote

$57 - $76.25/hr

Full-time

Posted 24 days ago

Job description

At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github.

About the Role

As a Cloud ML DevRel Engineer, your goal is to grow the impact of the Hugging Face ML Cloud team by teaching the community of ML practitioners how to accelerate their training and inference workloads.

The ML Cloud team works through strategic collaborations with the most widely used clouds (AWS, GCP, Azure, Cloudflare), AI accelerators (NVIDIA, AMD, Intel Gaudi, AWS Inferentia, TPU), and systems partners (Dell, Nutanix), to make it easy for the community to run Hugging Face models and libraries on these platforms. These partnerships sit at the core of our strategy as an open platform with no customer lock-in, and of how we drive usage and revenue for our partners.

This is a solid engineering role with a strong flavor of education and community. Your impact comes from driving visibility and usage of partner integrations, through work like:

  • Publishing technical blog posts
  • Contributing documentation and code examples
  • Speaking to business and technical audiences at partner conferences
  • Producing and running webinars
  • Building and showing off demos
  • Leading go-to-market conversations with strategic partners

You'll work at the front edge of generative AI and open source, hand in hand with some of the most important companies in the field. You'll have a lot of autonomy and full creative control, with the goal of having 10x the impact of a similar role at a big tech company.

About You

You're already an active voice in the ML community. You publish, you teach, and people follow your work on LinkedIn and X.

You care about ML engineering, building practical AI applications, shipping them to production, and squeezing the most out of the cloud to accelerate them. You like learning hard engineering concepts and talking them through with other engineers, and you take pride in code that's easy to read. You're a strong communicator and educator, and you enjoy engaging with the ML community in a positive, helpful way.

What you'll need
  • 3+ years in developer relations or developer advocacy, specifically for ML or AI products, tools, or platforms
  • An established public presence as a technical voice, with a track record of regularly publishing ML/AI content and a demonstrable, engaged audience on LinkedIn and X (Twitter)
  • A portfolio of developer-facing content you can point to: technical blog posts, conference talks, demos, code examples, or documentation
  • Comfort and experience with public speaking to technical audiences (conferences, webinars, workshops)
  • 3+ years of hands-on ML or software engineering experience, including taking models to production
  • Experience training or deploying ML models on at least one major cloud (AWS, GCP, or Azure)
  • Proficiency in Python
  • Practical experience with the Hugging Face stack (Transformers, the Hub, Inference Endpoints) or comparable open-source ML libraries
  • Working knowledge of GPUs or AI accelerators (NVIDIA, AMD, Intel Gaudi, AWS Inferentia, or TPU) and of training and inference optimization
  • Fluent written and spoken English
Nice to have
  • Open-source maintainer or contributor experience
  • An active presence in other developer communities (GitHub, Reddit, YouTube, Discord)
  • Familiarity with containers and orchestration (Docker, Kubernetes)
  • Experience with distributed training or inference-serving frameworks (for example vLLM, TGI, or Ray)
One more thing

At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “GPU-poor and proud