Cloud Machine Learning Developer Relations Engineer, Hugging Face
Community-driven platform for ML models
Be an early applicant
Community-driven platform for ML models
501-1000 employees
Be an early applicant
501-1000 employees
Company mission
Hugging Face is on a mission to democratize good machine learning, one commit at a time.
Role
Who you are
- 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
- 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
Desirable
- 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)
What the job involves
- 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
Our take
Large language models, which recognise and generate text, are already being used to auto-complete sentences, power chatbots, moderate content, summarise 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 personalised 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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