The Senior Product Software Engineer at Hugging Face will be responsible for building essential tooling for the Machine Learning Hub, working on technical challenges for ML-focused products, and collaborating across the stack using Typescript, Node.js, and other technologies.

As the first growth operations hire, you will develop go-to-market strategies, analyze customer data, manage partnerships, collaborate with engineering teams, and optimize operations for scalability. Your role is critical in shaping the company's growth by tracking metrics and guiding strategic decisions.

The ML Research Engineer Internship at Hugging Face involves working with the FineWeb team to develop high-quality web data through distributed data processing and training small models. The role focuses on enhancing dataset quality and contributing to the open-source ML community.

The Technical Solution Engineer will assist customers in integrating and debugging on Hugging Face Hub, maintain documentation, support internal usage, and help non-technical team members with advanced support requests. This role requires strong communication skills and the ability to navigate complex technical situations.

As an ML Research Engineer Intern at Hugging Face, you will work with the FineWeb team to create high-quality web data through distributed data processing and model training. This role emphasizes open-source contributions and aims to enhance accessibility to cutting-edge machine learning technologies.

Join Hugging Face's Optimization team as a Machine Learning Engineer, focusing on integrating state-of-the-art AI hardware with transformers models for improved performance and deploying them efficiently. You'll handle low-level system integrations and contribute to creating easy-to-use Python APIs, significantly impacting AI hardware and models.

The Growth Operations role at Hugging Face focuses on developing go-to-market strategies, managing customer data and trends, fostering partnerships, and optimizing operations for scalable growth. You will collaborate with engineering teams, report on growth metrics, and support the overall strategic direction of the company.

The internship focuses on expanding Hugging Face's ecosystem for web developers by creating and maintaining JavaScript/TypeScript machine learning libraries, optimizing models for in-browser inference, and building demo applications to showcase new features.

The Machine Learning Engineer Intern at Hugging Face is responsible for expanding tools that help users understand and write Gradio code, leveraging Gradio spaces and existing user prompts to build sophisticated model pipelines. The intern will experiment with modern deep learning libraries and LLM APIs to improve user experience and contribute to a growing community of developers.

The Machine Learning Engineer will develop specialized software for machine learning use cases, enhancing reliability and performance of the software suite while managing production environments. They will utilize existing frameworks to create scalable solutions and ensure overall system health, contributing ideas for real-world applications.

As a Cloud Machine Learning Engineer, you'll develop and integrate ML solutions leveraging cloud technologies. You'll work with Hugging Face libraries to create user-friendly APIs and write documentation, ensuring models meet performance standards.

As a Machine Learning Engineer Intern at Hugging Face, you will explore model usage to enhance the output quality from pre-trained models, focusing on integrating machine learning with software engineering and advancing generative AI techniques.

As a Senior UI Engineer at Hugging Face, you'll collaborate with the Product team to take ownership of product features, working on user experiences and design solutions for the HuggingFace Hub and other products, ensuring they meet market success and user needs.

As a Machine Learning Research Engineer Intern, you will work on creating agentic systems that utilize Large Language Models (LLMs) to improve GUI interactions. Your responsibilities include enhancing the agent framework, preparing datasets for fine-tuning, conducting model training, and releasing your work to the community.

As a Technical Solution Engineer at Hugging Face, you will assist customers in integrating and debugging on the Hugging Face Hub, develop documentation, and support both technical and non-technical users. You'll leverage your full-stack development experience with Javascript, Typescript, Node.js, and MongoDB while working autonomously and solving complex issues.

As a Machine Learning Optimization Evangelist, you'll educate ML practitioners about optimizing training and inference workloads. Collaborate with AI technology partners and contribute to documentation, technical blogs, and webinars. Drive visibility and engagement within the community while promoting Hugging Face's products through strategic partnerships.

The intern will focus on enhancing the quality output of existing small-sized pre-trained AI models. This role combines software engineering with machine learning engineering, tackling challenges related to model performance, hardware acceleration, and scalable software design.

As an ML Research Engineer Intern at Hugging Face, you will work on developing agentic systems that interact with GUIs via screen recordings and mouse/keyboard inputs. This role involves improving the agent framework, preparing fine-tuning datasets, and participating in large scale model training and inference orchestration, contributing to an open-source environment.

The Open-Source Machine Learning Engineer will enhance the open-source machine learning ecosystem using libraries like Transformers and Datasets. Responsibilities include interacting with users and contributors, fostering community engagement, and collaborating with researchers and data scientists to create impactful tools.

As a Machine Learning Engineer at Hugging Face, you will develop specialized software for real-world ML use cases using existing library frameworks. Your responsibilities include enhancing software reliability and performance, managing the production environment, and collaborating on innovative solutions.