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Hugging Face Jobs (NOW HIRING)

1 point system

GenAI Engineer

New York, NY · Remote

Expertise in Python and tools like Hugging Face, Langchain, and OpenAI API. Deep Learning Frameworks: Experience with TensorFlow, Keras, and PyTorch. Cloud Platforms: Familiar with Google Model ...

Hirekeyz Inc

Lead Engineer- Cloud Product

Alpharetta, GA · On-site

$100K - $131K/yr

Experienced with modern ML frameworks (TensorFlow, PyTorch, Hugging Face, etc.) and MLOps tools (Kubeflow, MLflow, Vertex AI Pipelines). * Proven record developing and deploying secure, enterprise ...

Frontier Technology Inc.

AI/ML Engineer

Chesapeake, VA · On-site +1

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 ...

Frontier Technology Inc.

AI/ML Engineer

Huntsville, AL · On-site +1

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 ...

E2B

Business Operations

San Francisco, CA · On-site

$200K - $230K/yr

Our customers include companies like Microsoft, Perplexity, Hugging Face, Manus, and Groq. We're building the next hyperscaler for AI agents. ABOUT E2B E2B is a fast-growing Series A startup with 8 ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

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 ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

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 ...

Tata Consultancy Service Limited

Engineer

Jersey City, NJ · On-site

$90K - $100K/yr

... Hugging Face, Llama Index etc. Good to have: - Working experience with Gemini LLM - Hands-on knowledge in machine learning frameworks like PyTorch, TensorFlow, Keras - Hands-On knowledge on NLP ...

Tata Consultancy Service Limited

Engineer

Irving, TX · On-site

$90K - $100K/yr

... Hugging Face, Llama Index etc. Good to have: - Working experience with Gemini LLM - Hands-on knowledge in machine learning frameworks like PyTorch, TensorFlow, Keras - Hands-On knowledge on NLP ...

Frontier Technology Inc.

AI/ML Engineer

Huntsville, AL · Remote

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 ...

Frontier Technology Inc.

AI/ML Engineer

Chesapeake, VA · Remote

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 ...

Berriehill Research

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems. * Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · On-site +1

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 ...

Frontier Technology Inc.

AI/ML Engineer

Huntsville, AL · Remote

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 ...

ReturnPro

AI/ML Engineer

Aventura, FL

Utilize tools like OpenAI API, Hugging Face, LangChain, LlamaIndex, and cloud platforms (AWS, Azure, GCP) for AI development and deployment. Required: · 5+ years of experience in AI/ML engineering ...

Frontier Technology Inc.

AI/ML Engineer

Chesapeake, VA · Remote

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 ...

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How much do hugging face jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for hugging face in the United States is $15.46, according to ZipRecruiter salary data. Most workers in this role earn between $12.98 and $18.27 per hour, depending on experience, location, and employer.

Can you make money on Hugging Face?

Hugging Face is a platform that offers opportunities for data scientists, machine learning engineers, and developers to monetize their skills through jobs, freelance projects, or contributing to open-source models. Earning potential depends on the type of work, experience, and whether you are employed directly or working independently. Building a strong portfolio and expertise in NLP and AI tools can increase income opportunities on the platform.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, educators, and skilled tradespeople, are likely to persist despite AI advancements. These roles often involve emotional intelligence, nuanced judgment, and hands-on skills that are difficult for AI to replicate. Continuous learning and adaptability remain important for job security in an evolving technological landscape.

What are Hugging Face jobs?

Hugging Face jobs refer to employment opportunities at the company focused on developing and maintaining open-source machine learning tools, especially in natural language processing. Roles may include software engineering, research, data science, and product management, often requiring skills in Python, deep learning frameworks, and collaboration in a tech environment.

How much do Hugging Face engineers make?

Hugging Face engineers' salaries vary based on experience, role, and location, but generally range from $100,000 to $180,000 annually. Senior positions and specialized roles in machine learning or software engineering tend to offer higher compensation, often including stock options and benefits.

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

More about Hugging Face jobs
What cities are hiring for Hugging Face jobs? Cities with the most Hugging Face job openings:
What states have the most Hugging Face jobs? States with the most job openings for Hugging Face jobs include:
What job categories do people searching Hugging Face jobs look for? The top searched job categories for Hugging Face jobs are:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $32,151 per year, or $15.5 per hour.

Lead Backend Architect Node.js, Cloud & AI

Stanley David and Associates

Manhattan, NY • On-site

Other

Posted 9 days ago

Job description

Role -  Lead Backend Architect – Node.js, Cloud & AI
Experience Required -10+ Years
 
 
Must Have Technical/Functional Skills:
 
• 10+ years of experience in designing and building enterprise-scale, cloud-native backend systems and distributed architectures.
• Strong hands-on expertise in Node.js, JavaScript, and TypeScript (must-have), with working knowledge of Python and Go.
• Extensive experience developing microservices, REST/gRPC APIs, event-driven architectures, and scalable backend platforms.
• Strong expertise in AWS and/or Google Cloud Platform, Kubernetes, Docker, cloud-native architecture, and CI/CD pipelines.
• Experience with distributed messaging and streaming technologies such as Kafka, queues, and asynchronous processing.
• Proven experience designing highly available, secure, scalable, and resilient backend systems.
• Strong understanding of databases (SQL/NoSQL), caching, observability, logging, and performance optimization.
• Mandatory experience integrating Large Language Models (LLMs) into enterprise applications and backend platforms.
• Hands-on experience with Agentic AI frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or Semantic Kernel.
• Experience building Retrieval-Augmented Generation (RAG) pipelines, AI orchestration workflows, and LLM gateways.
• Working knowledge of PyTorch, Hugging Face ecosystem, embeddings, inference, and model evaluation.
• Strong understanding of AI governance, evaluation, safety, and responsible AI practices.
• Excellent architecture, technical leadership, stakeholder management, and mentoring skills.
• Required Technologies
o Languages: Node.js, JavaScript, TypeScript, Python, Go
o Cloud: AWS/Google Cloud Platform
o Containers: Kubernetes, Docker
o APIs: REST, gRPC
o Messaging: Kafka or equivalent
o AI Frameworks: LangGraph, LangChain, LlamaIndex, CrewAI, Semantic Kernel
o ML: Hugging Face, PyTorch
o DevOps: CI/CD, Terraform (preferred)
 
Roles & Responsibilities
 
• Lead the architecture, design, and implementation of scalable cloud-native backend platforms for Lounge Services.
• Design and develop high-performance microservices and APIs using Node.js/TypeScript on AWS/Google Cloud Platform.
• Define architecture standards for distributed systems, event-driven solutions, messaging, and cloud-native applications.
• Drive the adoption of AI capabilities by integrating LLMs and Agentic AI into enterprise backend services.
• Design and implement reusable AI platform components including orchestration, RAG pipelines, model gateways, and AI observability.
• Provide technical leadership across engineering teams, driving architecture reviews, engineering best practices, and technology decisions.
• Collaborate with Product, Engineering, Security, and Enterprise Architecture teams to deliver scalable and secure solutions.
• Mentor engineering teams and influence technical direction across multiple initiatives.
• Evaluate emerging backend, cloud, and AI technologies and recommend enterprise adoption where appropriate.
• Ensure solutions meet enterprise standards for scalability, reliability, security, performance, and operational excellence. 

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