Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source, library of pre-trained models in the world. With more than 1 Million+ models and 320K+ stars on GitHub, over 15,000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly, and NASA.
Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are always looking to push the boundaries for faster, and more efficient ways to train and deploy models.
About the Role
We are looking for a Cloud Machine Learning engineer responsible to help build machine learning solutions used by millions leveraging cloud technologies. You will work on integrating Hugging Face's open-source libraries like Transformers and Diffusers, with major cloud platforms or managed SaaS solutions.
Responsibilities
Bridging and integrating transformers/diffusers models with different Cloud providers.
Ensuring the above models meet the expected performance.
Designing & Developing easy-to-use, secure, and robust Developer Experiences & APIs for our users.
Writing technical documentation, examples, and notebooks to demonstrate new features.
Sharing & Advocating your work and the results with the community.
About You
You'll enjoy working on this team if you have experience with and interest in deploying machine learning systems to production and building great developer experiences. The ideal candidate will have skills including:
Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets.
Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding.
Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents.
Experience in building MLOps pipelines for containerizing models and solutions with Docker.
Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful.
Ability to write clear documentation, examples, and definitions and work across the full product development lifecycle.
Bonus: Experience with Svelte & TailwindCSS.
More about Hugging Face
We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.
We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.
We support our employees wherever they are. While we have office spaces in NYC and Paris, we’re very distributed and all remote employees have the opportunity to visit our offices. If needed, we’ll also outfit your workstation to ensure you succeed.
We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.
We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

#J-18808-Ljbffr

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source, library of pre-trained models in the world. With more than 1 Million+ models and 320K+ stars on GitHub, over 15.000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly and NASA.
Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are always looking to push the boundaries for faster, and more efficient ways to train and deploy models.
About the Role
We are looking for a Cloud Machine Learning engineer responsible to help build machine learning solutions used by millions leveraging cloud technologies. You will work on integrating Hugging Face's open-source libraries like Transformers and Diffusers, with major cloud platforms or managed SaaS solutions.
Responsibilities
Bridging and integrating transformers/diffusers models with different Cloud providers.
Ensuring the above models meet the expected performance.
Designing & developing easy-to-use, secure, and robust Developer Experiences & APIs for our users.
Writing technical documentation, examples and notebooks to demonstrate new features.
Sharing & advocating your work and the results with the community.
About You
You'll enjoy working on this team if you have experience with and interest in deploying machine learning systems to production and building great developer experiences. The ideal candidate will have skills including:
Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets.
Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding.
Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents.
Experience in building MLOps pipelines for containerizing models and solutions with Docker.
Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful.
Ability to write clear documentation, examples and definitions and work across the full product development lifecycle.
Bonus: Experience with Svelte & TailwindCSS.
More about Hugging Face
We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.
We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.
We support our employees wherever they are. While we have office spaces in NYC and Paris, we’re very distributed and all remote employees have the opportunity to visit our offices. If needed, we’ll also outfit your workstation to ensure you succeed.
We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.
We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

#J-18808-Ljbffr

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source, library of pre-trained models in the world. With more than 1 Million+ models and 320K+ stars on GitHub, over 15.000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly and NASA.
Transformers in NLP pushed forward the computational requirements and the trend started to expand to other modalities such as Computer Vision and Speech which are actively adopting Transformer architectures to build the latest state-of-the-art models.
About the Role Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are always looking to push the boundaries for faster, and more efficient ways to train and deploy models.
If you like digging into the dark side of low-level system integrations, compiler support, and framework optimizations: we should talk!
We are looking for talented people to join the Hugging Face Special Ops team, focusing on:
Bridging transformers models with state-of-the-art AI hardware
Ensuring the above models meet the expected performance
Designing easy to use and proficient Developer Experience for our users
Deploying these models in the most efficient and scalable way.
This is an exciting opportunity to work at the edge of AI on both model architectures and hardware technologies!
About You You’ll enjoy working in this team if you like digging into the dark side of low-level system integrations, compiler support, and framework optimizations. At the intersection of software engineering and machine learning, you would be in charge of integrating the latest features from our hardware partners in Python/C++, designing rich and easy Python APIs in the continuity of what Hugging Face did with transformers, tokenizers, and the datasets library with a strong focus on performances. Linux or embedded devices experience would be a great plus for the job.
More about Hugging Face We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.
We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.
We support our employees wherever they are. While we have office spaces in NYC and Paris, we’re very distributed and all remote employees have the opportunity to visit our offices. If needed, we’ll also outfit your workstation to ensure you succeed.
We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.
We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

#J-18808-Ljbffr

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source, library of pre-trained models in the world. With more than 1 Million+ models and 320K+ stars on GitHub, over 15,000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly and NASA.
Transformers in NLP pushed forward the computational requirements and the trend started to expand to other modalities such as Computer Vision and Speech which are actively adopting Transformer architectures to build the latest state-of-the-art models.
About the Role Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are always looking to push the boundaries for faster, and more efficient ways to train and deploy models.
If you like digging into the dark side of low-level system integrations, compiler support, and framework optimizations: we should talk!
We are looking for talented people to join the Hugging Face Special Ops team, focusing on:
Bridging transformers models with state-of-the-art AI hardware
Ensuring the above models meet the expected performance
Designing easy to use and proficient Developer Experience for our users
Deploying these models in the most efficient and scalable way.
This is an exciting opportunity to work at the edge of AI on both model architectures and hardware technologies!
About You You’ll enjoy working in this team if you like digging into the dark side of low-level system integrations, compiler support, and framework optimizations. At the intersection of software engineering and machine learning, you would be in charge of integrating the latest features from our hardware partners in Python/C++, designing rich and easy Python APIs in the continuity of what Hugging Face did with transformers, tokenizers, and the datasets library with a strong focus on performances. Linux or embedded devices experience would be a great plus for the job.
More about Hugging Face We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.
We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.
We support our employees wherever they are. While we have office spaces in NYC and Paris, we’re very distributed and all remote employees have the opportunity to visit our offices. If needed, we’ll also outfit your workstation to ensure you succeed.
We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.
We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

#J-18808-Ljbffr

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source library of pre-trained models in the world. With more than 1 Million+ models and 320K+ stars on GitHub, over 15,000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, Grammarly, and NASA.
About the role:

As a Machine Learning Engineer, you will work mainly on creating great libraries highly focused on real-world ML use cases. We're building on top of our open-source to create more specialized code with a focus on industrial-level usage.
We are searching for someone who brings fresh ideas, demonstrates a unique and informed viewpoint, and enjoys collaborating with a progressive, nimble, and decentralized approach to develop real-world solutions and positive user experiences at every interaction.
Objectives of this role:
Develop specialized software for specific machine learning (ML) use cases that have broad applications, similar to text-generation-inference .
Utilize existing library frameworks to create scalable software solutions for industrial purposes.
Enhance the reliability, quality, and time-to-market of our software suite. Measure and optimize system performance to stay ahead of customer needs and drive innovation.
Manage the production environment by monitoring availability and ensuring overall system health.
About you:
If you are a passionate Machine Learning Engineer with a keen interest in AI and proficient with Python, Rust, and specialized CUDA kernels (transformers, Keras, or PyTorch), we would love to hear from you. Join our team and contribute to the advancement of AI technologies while working alongside talented professionals in a collaborative and stimulating environment.

#J-18808-Ljbffr

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source, library of pre-trained models in the world. With more than 1 Million+ models and 320K+ stars on GitHub, over 15,000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, Grammarly and NASA.
About the role:

As a Machine Learning Engineer, you will work mainly on creating great libraries highly focused on real-world ML use cases. We're building on top of our open-source to create more specialized code with a focus on industrial levels of usage.
We are searching for someone who brings fresh ideas, demonstrates a unique and informed viewpoint, and enjoys collaborating with a progressive, nimble, and decentralized approach to develop real-world solutions and positive user experiences at every interaction.
Objectives of this role:
Develop specialized software for specific machine learning (ML) use cases that have broad applications, similar to text-generation-inference .
Utilize existing library frameworks to create scalable software solutions for industrial purposes.
Enhance the reliability, quality, and time-to-market of our software suite. Measure and optimize system performance to stay ahead of customer needs and drive innovation.
Manage the production environment by monitoring availability and ensuring overall system health. We run our own tools.
About you:
If you are a passionate Machine Learning Engineer with a keen interest in AI and proficient with Python, Rust, and specialized CUDA kernels Frameworks (transformers of course + Keras or PyTorch), we would love to hear from you. Join our team and contribute to the advancement of AI technologies while working alongside talented professionals in a collaborative and stimulating environment.
More about Hugging Face
We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.
We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer flexible parental leave and paid time off.
We support our employees wherever they are. While we have office spaces in NYC and Paris, we're very distributed, and all remote employees have the opportunity to visit our offices. If needed, we'll also outfit your workstation to ensure you succeed.
We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.
We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

#J-18808-Ljbffr

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Machine Learning Engineer Hugging Face Jobs

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