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Face Models 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 ...

IntraEdge

Sr. Engineer - Backend

Woonsocket, RI

Collaborate with data science and product teams to incorporate pre-trained LLMs (e.g., OpenAI, Hugging Face models) into backend workflows * Participate in system architecture discussions ...

Vytwo

Lead AI Engineer - Bengaluru, INDIA

Prosper, TX · On-site +1

$93K - $123K/yr

Fine-tune LLMs using LoRA/QLoRA and integrate with Azure OpenAI or Hugging Face models. * Implement vector search and retrieval pipelines using FAISS or Azure Cognitive Search. * Ensure responsible ...

IBM

Customer Success Engineer Co-op Fall 2026

Dallas, TX · On-site

... Face models via APIs) and LLM inference (batch vs. real-time). • Understanding of model fine-tuning and in-context learning (choosing when to prompt-engineer vs. train) as part of the LLM lifecycle ...

PermitFlow

Applied Machine Learning Engineer

New York, NY · Remote

$175K - $250K/yr

Deep expertise in NLP and LLMs (OpenAI GPT, Claude, Hugging Face models) * Experience building retrieval and vector search systems (e.g., FAISS, Elasticsearch, Pinecone, Weaviate) * Proficiency in ...

PermitFlow

Applied Machine Learning Engineer

New York, NY · On-site

$175K - $250K/yr

Deep expertise in NLP and LLMs (OpenAI GPT, Claude, Hugging Face models) * Experience building retrieval and vector search systems (e.g., FAISS, Elasticsearch, Pinecone, Weaviate) * Proficiency in ...

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How much do face models jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for face models in the United States is $45.71, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $72.12 per hour, depending on experience, location, and employer.

What are some common challenges face models encounter during photo shoots and how can they prepare for them?

Face models often face challenges such as maintaining natural expressions for extended periods, adapting to diverse makeup styles, and working under various lighting conditions. To prepare, it's helpful to practice facial flexibility in front of a mirror, take care of skin health, and understand how to communicate effectively with photographers and makeup artists. Building resilience and comfort in front of the camera can also help face models deliver consistent results even during long or demanding shoots.

What is the difference between Face Models vs Makeup Models?

AspectFace ModelsMakeup Models
Required CredentialsMinimal; often based on appearance and skin conditionMinimal; focus on makeup application and skin suitability
Work EnvironmentPhoto shoots, fashion shows, advertisingPhoto shoots, beauty campaigns, runway shows
Industry UsageFashion, advertising, beautyBeauty, cosmetics, fashion
Search & Comparison IntentPeople seeking face modeling opportunities or infoPeople comparing face models and makeup models roles

Face models primarily focus on showcasing facial features for various media, requiring minimal credentials. Makeup models, on the other hand, are used to display makeup products and techniques. Both roles are common in fashion and beauty industries, often overlapping in photo shoots and campaigns. Understanding these differences helps individuals identify the right modeling path based on their appearance and career goals.

What Do Face Models Do?

Face models pose for head shots to showcase products like makeup and jewelry. As a face model, you may make a variety of facial expressions to demonstrate how a product looks under varying circumstances or help to highlight the product’s features for marketing purposes. You frequently work with new products, take instruction from a photographer, and hold poses or expressions for extended periods. This job title is also used for motion capture roles designed to help create more realistic CGI in movies, video games, and other types of media. Face modeling jobs should not be confused with using clay or other materials to create models of faces.

What are face models?

Face models are individuals whose facial features are used to promote products, brands, or services, especially in the beauty, skincare, and cosmetics industries. Their main job is to have their faces photographed or filmed for advertisements, magazines, commercials, and promotional campaigns. Face models are chosen for their unique or appealing facial characteristics, symmetry, and ability to express a range of emotions. Unlike traditional fashion models who may showcase clothing on runways, face models focus primarily on close-up shots that highlight their facial features. They often work with photographers, makeup artists, and brands to create compelling visual content.

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 distinctive facial features, well-maintained skin, and a professional portfolio, with experience or representation by a reputable modeling agency often preferred. Familiarity with posing techniques, camera work, and sometimes basic makeup application are important technical skills, while attending casting calls may require knowledge of industry booking platforms. Confidence, adaptability, and the ability to take direction well are essential soft skills that set successful face models apart. These attributes ensure models can consistently deliver the desired looks for clients, maintain professionalism during demanding shoots, and build a lasting reputation in the competitive modeling industry.
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Face Models jobs near you
Infographic showing various Face Models job openings in the United States as of May 2026, with employment types broken down into 81% Full Time, 18% Part Time, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $95,086 per year, or $45.7 per hour.
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 27 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