At a Glance
- Tasks: Design new information architectures and train language models to optimize data interaction.
- Company: Join a cutting-edge team focused on redefining how AI interacts with data.
- Benefits: Collaborate with top ML researchers and enjoy a flexible, innovative work environment.
- Why this job: Be at the forefront of AI development and make a real societal impact.
- Qualifications: Expertise in Python, machine learning, and experience with Large Language Models required.
- Other info: Pair programming is encouraged, fostering teamwork and collaboration.
The predicted salary is between 48000 - 72000 £ per year.
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 role:
We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures.
Responsibilities:
- Designing and implementing from scratch new information architecture strategies
- Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
- Building \”hard\” knowledge base eval sets to help identify failure modes of how language models work with external data
- Designing and evaluating advanced agentic search capabilities.
You may be a good fit if you:
- Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
- Have good machine learning research experience
- Have experience developing software that utilizes Large Language Models such as Claude
- 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 partner with world-class ML researchers to develop new LLM capabilities
- Care about the societal impacts of your work
- Have clear written and verbal communication
Strong candidates will also have experience with:
- Collaborating with product teams to quickly prototype and deliver innovative solutions
- Building complex agentic systems that utilize LLMs
- Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing
The expected salary range for this position is:
Annual Salary:
£250,000-£340,000 GBP
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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Research Engineer, Knowledge Team employer: Anthropic
Contact Detail:
Anthropic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer, Knowledge Team
✨Tip Number 1
Familiarize yourself with the latest advancements in Large Language Models (LLMs) and their applications. Understanding how these models interact with data sources will give you a significant edge in discussions during the interview process.
✨Tip Number 2
Showcase your experience with Python programming by preparing examples of your past projects. Be ready to discuss how your code has positively impacted team workflows or project outcomes, as this aligns with our emphasis on high-quality, reliable code.
✨Tip Number 3
Highlight any collaborative experiences you've had with product teams. Being able to demonstrate your ability to quickly prototype and deliver innovative solutions will resonate well with us, as we value flexibility and impact.
✨Tip Number 4
Prepare to discuss the societal impacts of your work in machine learning. We care about how our technologies affect the world, so showing that you share this concern will make you stand out as a candidate who aligns with our values.
We think you need these skills to ace Research Engineer, Knowledge Team
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and requirements. Highlight your experience with Python programming, machine learning, and LLMs in your application.
Tailor Your CV: Customize your CV to emphasize relevant skills and experiences that align with the role. Focus on your programming expertise, any projects involving LLMs, and your ability to collaborate with teams.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the role and the impact of your work. Mention specific examples of how you've designed information architectures or worked with machine learning models.
Showcase Communication Skills: Since clear written and verbal communication is crucial, ensure your application materials are well-organized and free of errors. Consider including a brief section on how you’ve effectively communicated complex ideas in past projects.
How to prepare for a job interview at Anthropic
✨Showcase Your Python Skills
As a Research Engineer, you'll need to demonstrate your proficiency in Python. Be prepared to discuss specific projects where you've produced reliable and high-quality code, and consider sharing examples that highlight your ability to work collaboratively with teammates.
✨Discuss Your Machine Learning Experience
Make sure to articulate your machine learning research experience clearly. Talk about any projects involving Large Language Models, especially Claude, and how you approached challenges in developing software that utilizes these models effectively.
✨Emphasize Flexibility and Results Orientation
The role requires a results-oriented mindset with a bias towards flexibility. Prepare to share instances where you've adapted to changing requirements or taken initiative beyond your job description to achieve impactful results.
✨Prepare for Technical Discussions
Expect technical questions related to information architecture strategies and agentic systems. Brush up on your knowledge of advanced search capabilities and be ready to discuss how you've implemented or evaluated such systems in the past.