Research Engineer / Research Scientist, Multimodal

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.

You want to build cutting edge Artificial Intelligence from the ground up. You are passionate that these systems are safe and trustworthy, and care about their broader societal impact. In this role, you'll work on research, development, and infrastructure for state-of-the-art large language models, with a focus on multimodal capabilities. This role will touch all parts of the research ecosystem, from building infrastructure to developing research prototypes to running multi-thousand accelerator training jobs.You may be a good fit if some of the following apply to you:

• Care deeply about the societal impacts of your work
• Want to work on the frontier of Artificial Intelligence
• Have substantial software engineering experience through industry, academia, or other projects
• Have research experience, through writing scientific publications, or involvement in personal or industrial projects
• Are results oriented and flexible in your approach
• Are willing to pick up slack, even if it goes outside your job description
• Like working in a close-knit team environment, and enjoy pair programming!

Strong candidates may have experience with some of the following:

• High performance, large-scale Machine Learning systems
• ML hardware, frameworks, and infrastructure, such as TPUs, GPUs, Jax, PyTorch, OS internals, and Kubernetes
• Language modeling with transformers
• Deep learning research on images, videos, audio, or other modalities

Representative projects:

• Design a training loss for a new modality
• Design and run experiments to evaluate the scalability of two architectural variants
• Analyze and debug a large-scale training run
• Scale an architecture to optimize throughput on thousands of GPUs
• Build from-scratch a new deep learning architectural components
• Build a pipeline to ingest a novel source of data
• Build a language model evaluation
• Build a tool for data visualization
• Review the scientific literature in a domain write a design doc on how techniques could be applied

Logistics

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.