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- Tasks: Join our team to build and study multimodal AI models for safety research.
- Company: Anthropic is dedicated to developing safe and impactful AI technologies.
- Benefits: Enjoy flexible work options, collaborative culture, and opportunities for personal growth.
- Why this job: Be part of groundbreaking research that shapes the future of AI and its societal impact.
- Qualifications: Significant software engineering experience; passion for machine learning and societal impacts.
- Other info: We welcome both experienced engineers and enthusiastic researchers to apply.
The predicted salary is between 36000 - 60000 £ per year.
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, and 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
Research Engineer / Research Scientist, Multimodal employer: Anthropic
Contact Detail:
Anthropic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer / Research Scientist, Multimodal
✨Tip Number 1
Familiarise yourself with the latest advancements in multimodal AI. Read up on recent research papers and case studies that highlight how multimodal models are being developed and applied. This will not only enhance your understanding but also give you talking points during interviews.
✨Tip Number 2
Engage with the community by participating in forums or attending conferences related to AI and machine learning. Networking with professionals in the field can provide insights into the company culture at Anthropic and may even lead to referrals.
✨Tip Number 3
Showcase any relevant projects or experiences that demonstrate your ability to work with multimodal data. Whether it's through personal projects, contributions to open-source, or previous job roles, having concrete examples will make you stand out.
✨Tip Number 4
Prepare for technical discussions by brushing up on your software engineering skills, particularly in areas like Python, Pytorch, and Kubernetes. Being able to discuss your technical expertise confidently will be crucial during the interview process.
We think you need these skills to ace Research Engineer / Research Scientist, Multimodal
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description for the Research Engineer / Research Scientist position at Anthropic. Familiarise yourself with the key responsibilities and required skills, especially in multimodal AI systems.
Tailor Your CV: Customise your CV to highlight relevant experience in software engineering, machine learning, and any specific technologies mentioned, such as GPUs or Pytorch. Make sure to showcase projects that demonstrate your ability to work with multimodal data.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for AI safety research and your understanding of its societal impacts. Mention specific experiences that align with the role's focus areas, like foundational research or data ingestion.
Showcase Collaboration Skills: Since the team values pair programming and collaboration, include examples in your application that demonstrate your teamwork abilities and how you've successfully worked with others on complex projects.
How to prepare for a job interview at Anthropic
✨Understand the Multimodal Landscape
Familiarise yourself with multimodal AI systems and their applications. Be prepared to discuss how different data types, like images and audio, can interact with text-based models. This shows your understanding of the role's core focus areas.
✨Showcase Your Engineering Experience
Highlight your software engineering background during the interview. Discuss specific projects where you’ve built or worked on large-scale ML systems, especially if they involved GPUs, Kubernetes, or Pytorch. Concrete examples will demonstrate your capability.
✨Emphasise Collaboration Skills
Since the team values pair programming, be ready to talk about your experiences working collaboratively. Share instances where you picked up tasks outside your usual responsibilities, showcasing your flexibility and team spirit.
✨Discuss Societal Impacts
Express your awareness of the societal implications of AI technology. Prepare to discuss how you would approach safety research and risk mitigation in multimodal AI systems, aligning with the company's mission and values.
