Cloud Machine Learning Engineer, Hugging Face
Community-driven platform for ML models
Job no longer available
Community-driven platform for ML models
501-1000 employees
Job no longer available
501-1000 employees
Company mission
To democratize good machine learning.
Role
Who you are
- You'll enjoy working on this team if you have experience with and interest in deploying machine learning systems to production and build great developer experiences
- 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 definition and work across the full product development lifecycle
- Bonus: Experience with Svelte & TailwindCSS
What the job involves
- 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
- Bridging & Integrating transformers/diffusers models with a different Cloud provider
- Ensuring the above models meet the expected performance
- Designing & Developing easy-to-use, secure, and robust Developer Experiences & APIs for our users
- Sharing & Advocating your work and the results with the community
Our take
Large language models, which recognize and generate text, are already being used to auto-complete sentences, power chatbots, moderate content, summarize news articles, and translate text online. However, many of these advances are happening behind closed doors, stifling innovation and raising ethical concerns.
To combat this, Hugging Face is building the "GitHub of machine learning". It’s a community-driven platform with a ton of repositories, where developers can create, discover and collaborate on ML models, datasets and ML apps. This work led to the creation of BLOOM in 2022, an open-access LLM with similar architecture to OpenAI’s GPT, but that is multilingual by design.
The company also launched the Hugging Chat Assistant, an open-source tool creating personalized chat assistants, in direct competition with OpenAI's paid service ChatGPT Plus. By continually creating value based on a global community, not just for Microsoft or Google, HuggingFace should be able to carve out its own path for success.
Freddie
Company Specialist at Welcome to the Jungle
Insights
36% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Aug 2023
$235m
SERIES D
May 2022
$100m
SERIES C
Total funding: $395.8m
Company benefits
- Flexible Work Environment
- Health Insurance
- Unlimited PTO
- Equity
- Growth, Training, & Conferences
- Generous Parental Leave
Company HQ
Dumbo, NY
Leadership
Clem Delangue
(Co-Founder & CEO)Created Moodstocks, a startup building machine learning for computer vision acquired by Google. Also built Mention where they were head of Product and CMO until the company was acquired by MyNewsDesk.
Julien Chaumond
(Co-Founder & CTO)Former advisor for the Deputy Minister for Digital Affairs in Paris, and Senior engineer for Stupefix app that was acquired by GoPro. Also co-founded and was CTO of Glose.
Thomas Wolf
(Co-Founder & CSO)After graduating from Ecole Polytechnique, they worked on laser-plasma interactions at the BELLA Center of the Lawrence Berkeley National Laboratory. Also worked as a European Patent Attorney for 5 years.
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