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ML Research Engineer, AI Agents - EMEA Remote

At Hugging Face, we’re on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 5 million users & 100k organizations who collectively shared over 1M models, 300k datasets & 300k apps. Our open-source libraries have more than 400k+ stars on Github.

About the Role

2025 will be the year of Agents.

LLM agents, what are these? In short, agentic systems are a way to connect an LLM to the outside world, to let it perform actions and observations. The promises of such a setup are immense : it enables an LLM to get external knowledge to ground its reasoning, use reliable tools for specific tasks, and even self-correct errors through additional iterations. An agentic system requires a powerful enough LLM to reason and plan actions. Now with the progress of LLMs in general and specifically open models overtaking closed ones, we have all the weapons to build great agents.

So Hugging Face is launching a moonshot in that direction. We’ve already published the library smolagents, gathering 4k stars in a few days at the time of writing. 

On top of keeping the momentum with smolagents, we intend to launch a new direction of effort : GUI agents, i.e. agents that take screen recordings from any GUI, and act through a mouse/keyboard setup. You may have seen such models from other companies: we’ll make them better and open, building all the stack necessary towards efficient GUI agents, and open-sourcing useful building blocks that we made along the way.

What you will do

Building agents is both exciting and challenging as it lies at the intersection of post-training, inference, orchestration as well as UX design. This job will include the whole agent stack, including:

  • Maintain and improve smolagents
  • Build libraries and code around agents and GUI agents
  • Prepare fine-tuning datasets, training recipes, and inference orchestration.
  • Leverage our large H100 cluster for large scale processing and model training.
  • Release any code we built, as well as the model serving as a foundation for the community to build on, possibly as a new GUI agent framework and/or research papers.
  • Collaborate and empower the community to build on top of our tools.

At Hugging Face, everything you do will have an outsized impact. Every employee is empowered to take important decisions, and every decision has a global reach thanks to our massive open-source community. This is the place on Earth where you have the best chances to make a 1000x impact.

About You

You'll enjoy working here if you are:

  • Enthusiastic about agents.
  • Are a generalist engineer with an ability to pick up new frameworks quickly and willing to work across the stack, from framework maintenance to model training to redacting research reports.
  • Comfortable working in a fast-paced and ambiguous environment, aka shifting sands of startup land. This includes communicating with other teams to efficiently join forces, in Hugging Face’s very decentralized/anarchic organization.
  • Excited to be a builder for builders! Empathy for developers across the stack and an enthusiasm for developer-first products.
  • Enjoy understanding technical domains deeply and are willing to really get into the weeds.

If you're interested in joining us, but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact.

Checkout hf.co/science for more information about the science team at Hugging Face.

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 toward 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. However, this job offer is quite special as it's best if you are in-person in our new Paris office. We provide relocation packages if necessary.

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.

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What You Should Know About ML Research Engineer, AI Agents - EMEA Remote, Hugging Face

At Hugging Face, we've embarked on an exciting mission to democratize AI, and we’re looking for an enthusiastic ML Research Engineer to join our emerging AI Agents team! This remote position offers the chance to be part of a movement that is rapidly gaining traction with over 5 million users and 100,000 organizations already on board. Imagine working at the intersection of LLMs and agentic systems—where the potential for growth and innovation is immense. As an ML Research Engineer, you will dive into the realm of building agentic systems, connecting language models to the world and enabling them to perform tasks while learning and refining their outputs. You'll maintain and enhance our growing smolagents library and be part of a pioneering new direction focused on GUI agents. This role is about hands-on development, from crafting fine-tuning datasets to leveraging our powerful H100 cluster for intense computational tasks. At Hugging Face, we believe in empowerment. Every member has a voice, and your contributions will ripple through our global open-source community. If you love the sense of ownership and making meaningful changes, this is the right place for you. Join us, and together we will make a 1000x impact. Your curiosity and drive can really shape the future of AI at Hugging Face!

Frequently Asked Questions (FAQs) for ML Research Engineer, AI Agents - EMEA Remote Role at Hugging Face
What are the main responsibilities of a ML Research Engineer at Hugging Face?

As a ML Research Engineer at Hugging Face, your primary responsibilities will include maintaining and improving our smolagents library, building libraries and code for agentic systems, preparing fine-tuning datasets, and orchestrating inference processes. You'll also work on large-scale processing and model training using our H100 cluster and collaborate with the community to develop useful tools and frameworks.

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What qualifications are necessary to become a ML Research Engineer at Hugging Face?

To qualify for the ML Research Engineer position at Hugging Face, you should possess a strong background in machine learning and engineering principles. Familiarity with frameworks and a willingness to learn new technologies are essential. Experience in working with large language models and a deep understanding of technical domains are valuable assets for driving impactful projects.

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What kind of work culture can I expect as a ML Research Engineer at Hugging Face?

At Hugging Face, the work culture is dynamic, decentralized, and nurturing. You will be part of a community that values diversity, equity, and inclusivity. Employees are encouraged to take initiative and make important decisions that influence the global AI landscape, highlighting the collaborative spirit and shared passion for innovation.

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How does Hugging Face support professional development for ML Research Engineers?

Hugging Face is deeply committed to the professional growth of its team members. We offer reimbursement for relevant conferences, training, and education to ensure you stay at the cutting edge of machine learning and AI advancements. Our culture promotes continuous learning and collaboration, fostering an environment perfect for developers and researchers alike.

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What is the expected impact of the ML Research Engineer role on Hugging Face's future?

The ML Research Engineer role at Hugging Face is pivotal for shaping the future of AI. With responsibilities that include developing agentic systems, your contributions will directly influence the capabilities of machine learning models, empowering our open-source community and potentially redefining the landscape of AI applications.

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Common Interview Questions for ML Research Engineer, AI Agents - EMEA Remote
Can you describe your experience with large language models and their applications?

When discussing your experience with large language models, emphasize specific projects you've worked on, the challenges you faced, and how you overcame them. Highlight your understanding of model training, fine-tuning, and the practical applications you've developed, showcasing your hands-on involvement in real-world scenarios.

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What interests you most about building agentic systems?

When responding about your interest in agentic systems, share your fascination with their potential to transform user interactions. Discuss how you envision their applications in real-world tasks and express your excitement about being part of the innovative journey that Hugging Face is undertaking.

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How do you approach collaboration with other teams in a decentralized organization?

In answering this question, illustrate your communication strategies and collaborative methods. Emphasize your adaptability and openness to feedback, stressing how building relationships across teams can lead to fruitful collaborations and innovative solutions.

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What strategies do you use for maintaining code quality and documentation?

When addressing code quality, outline the practices you follow, such as code reviews, testing methods, and documentation standards. Stress the importance of well-documented code for community contributions, making it clear you understand its impact on collaborators and future developments.

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Explain how you would handle an ambiguous project requirement.

Share your approach to dealing with uncertainty, perhaps by starting with thorough research and gathering information from stakeholders. Highlight your ability to make informed decisions and iterate based on feedback, demonstrating a proactive mindset in project management.

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How do you stay updated with the latest trends in AI and machine learning?

Detail your strategies for keeping abreast of industry developments, such as following select publications, participating in forums, attending conferences, and engaging with AI communities online. Illustrate your passion for continuous learning in the ever-evolving field of AI.

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What tools and frameworks are you most comfortable working with?

Mention the specific programming languages, ML frameworks, and tools you have experience with. Explain how you’ve leveraged these tools in past projects and your readiness to adapt to new technologies based on project needs.

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Can you provide an example of a successful project you led and its impact?

Select a project that demonstrates your leadership and technical skills. Discuss the objectives, your role in driving it to success, and the measurable impact it had on your team or organization. This illustrates your ability to take initiative and deliver results.

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Why do you want to work with Hugging Face's open-source community?

Express your commitment to open-source principles and how you value community contributions. Discuss how working at Hugging Face aligns with your vision of collaboration and innovation in AI, emphasizing your desire to empower developers and researchers through accessible tools.

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What makes you a good fit for the ML Research Engineer role at Hugging Face?

Summarize your relevant skills, experiences, and alignment with the core values of Hugging Face. Highlight your passion for AI and your unique perspective, ensuring you convey how you can contribute to the company's missions and goals.

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Full-time, remote
DATE POSTED
January 8, 2025

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