Job Application for Research Engineer / Research Scientist, Pre-training at Anthropic

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About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the team

We are seeking passionate Research Scientists and Engineers to join our growing Pre-training team in Zurich. We are involved in developing the next generation of large language models. The team primarily focuses on multimodal capabilities: giving LLMs the ability to understand and interact with modalities other than text.

In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

Responsibilities

In this role you will interact with many parts of the engineering and research stacks.

Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
Independently lead small research projects while collaborating with team members on larger initiatives
Design, run, and analyze scientific experiments to advance our understanding of large language models
Optimize and scale our training infrastructure to improve efficiency and reliability
Develop and improve dev tooling to enhance team productivity
Contribute to the entire stack, from low-level optimizations to high-level model design

Qualifications & Experience

We encourage you to apply even if you do not believe you meet every single criterion. Because we focus on so many areas, the team is looking for both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer spectrum to apply.

Degree (BA required, MS or PhD preferred) in Computer Science, Machine Learning, or a related field
Strong software engineering skills with a proven track record of building complex systems
Expertise in Python and deep learning frameworks
Have worked on high-performance, large-scale ML systems, particularly in the context of language modeling
Familiarity with ML Accelerators, Kubernetes, and large-scale data processing
Strong problem-solving skills and a results-oriented mindset
Excellent communication skills and ability to work in a collaborative environment

You'll thrive in this role if you

Have significant software engineering experience
Are able to balance research goals with practical engineering constraints
Are happy to take on tasks outside your job description to support the team
Enjoy pair programming and collaborative work
Are eager to learn more about machine learning research
Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
Have ambitious goals for AI safety and general progress in the next few years, and you’re excited to create the best outcomes over the long-term

Sample Projects

Optimizing the throughput of novel attention mechanisms
Proposing Transformer variants, and experimentally comparing their performance
Preparing large-scale datasets for model consumption
Scaling distributed training jobs to thousands of accelerators
Designing fault tolerance strategies for training infrastructure
Creating interactive visualizations of model internals, such as attention patterns

If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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Are you open to working in-person in one of our offices 25% of the time?

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Of the locations listed on the job posting, which one are you most interested in working from for your 25% time in-person?

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When is the earliest you would want to start working with us?

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AI Policy for Application

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While we encourage people to use AI systems during their role to help them work faster and more effectively, please do not use AI assistants during the application process. We want to understand your personal interest in Anthropic without mediation through an AI system, and we also want to evaluate your non-AI-assisted communication skills. Please indicate 'Yes' if you have read and agree.

Why Anthropic?

Why do you want to work at Anthropic? (We value this response highly - great answers are often 200-400 words.)

In one paragraph, provide an example of something meaningful that you have done in line with your values. Examples could include past work, volunteering, civic engagement, community organizing, donations, family support, etc.

Team Matching *

Pre-training — The Pre-training team trains large language models that are used by our product, alignment, and interpretability teams. Some projects include figuring out the optimal dataset, architecture, hyper-parameters, and scaling and managing large training runs on our cluster.

AI Alignment Research — the Alignment team works to train more aligned (helpful, honest, and harmless) models and does “alignment science” to understand how alignment techniques work and try to extrapolate to uncover and address new failure modes.

Reinforcement Learning – Reinforcement Learning is used by a variety of different teams, both for alignment and to teach models to be more capable at specific tasks.

Platform – The Platform team builds shared infrastructure used by Anthropic's research and product teams. Areas of ownership include: the inference service that generates predictions from language models; extensive continuous integration and testing infrastructure; several very large supercomputing clusters and the associated tooling.

Interpretability — The Interpretability team investigates what’s going on inside large language models — in a sense, they are trying to reverse engineer the concepts and mechanics from the inscrutable learned weights of these systems. Their goal is to ensure that AI systems are safe by being able to assess whether they’re doing what we actually want, all the way down to the individual neurons.

Societal Impacts — Our Societal Impacts team designs and executes experiments that evaluate the capabilities and harms of the technologies we build. They also support the policy team with empirical evidence.

Product — The Product research team trains, evaluates, and improves upon Claude, integrating all of our research techniques to make our AI systems as safe and helpful as possible.

Which teams or projects are you most interested in? (Note: if none of the teams you select are hiring, we won't proceed with your application at this time, although we may reach out if those teams open roles in the future.)

What’s your ideal breakdown of your time in a working week, in terms of hours or % per week spent on meetings, coding, reading papers, etc.?

Will you now or will you in the future require employment visa sponsorship to work in the country in which the job you're applying for is located?

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Additional Information

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Research Engineer / Research Scientist, Pre-training

About Anthropic

About the team

Responsibilities

Qualifications & Experience

You'll thrive in this role if you

Sample Projects

Logistics

How we're different

Come work with us!

Apply for this job