Research Engineer / Research Scientist, Multimodal

Anthropic; Greater London; On-site; GBP 50,000 - 100,000; Full time

Job summary

Join a forward-thinking company dedicated to advancing AI safety through innovative multimodal research. This exciting role involves building and studying cutting-edge multimodal models that integrate various data types, such as images, video, and audio. As part of a dynamic team, you'll contribute to foundational research, infrastructure projects, and data ingestion processes, all while collaborating closely with experienced engineers and researchers. If you're passionate about software engineering and eager to explore the societal impacts of AI, this opportunity is perfect for you. Embrace the chance to make a meaningful impact in the rapidly evolving field of AI!

Qualifications

• Significant software engineering experience is essential.
• Interest in machine learning research and societal impacts is a plus.

Responsibilities

• Develop new architectures for multimodal data modeling.
• Build infrastructure for multimodal reinforcement learning environments.

Skills

Software Engineering

Machine Learning Research

Reinforcement Learning

Pair Programming

Large-scale ML Systems

Data Processing

Kubernetes

Pytorch

Language Modeling

Tools

GPUs

ETL Tools

Job description

At Anthropic, we believe the most impactful safety research will require access to frontier AI systems. The most powerful AIs will operate not just on text but also other modes of data, including images, video and audio.Such models have potential to augment human creativity and productivity in exciting ways. However, we are very concerned about the risks introduced by powerful multimodal AIs. The Multimodal team at Anthropic builds and studies multimodal models to better understand and mitigate these risks.

Our team works across many parts of a large stack that includes training, inference, system design and data collection. Some of our core focus areas are:

Foundational Research

We develop new architectures for modeling multimodal data and study how they interact with text-only models at scale.

Building Infrastructure

We work on many infrastructure projects including:

• Complex multimodal reinforcement learning environments.
• High-performance RPC servers for processing image inputs.
• Sandboxing infrastructure for securely collecting data.

Data Ingestion

We are more interested in running simple experiments at large scale than smaller complex experiments. This requires access to very large sources of multimodal data. We develop tooling to collect, process and clean multimodal data at scale.

Because we focus on so many areas, the team is looking to work with both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer curve to apply.

You may be a good fit if you:

• Have significant software engineering experience
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPUs, Kubernetes, Pytorch, or OS internals
• Language modeling with transformers
• Reinforcement learning
• Large-scale ETL