At a Glance
- Tasks: Redesign how Language Models interact with data and create innovative information architectures.
- Company: Join a cutting-edge AI company focused on societal impacts and diverse perspectives.
- Benefits: Competitive salary, equity options, unlimited PTO, and comprehensive health benefits.
- Other info: Collaborate with world-class researchers in a dynamic, inclusive environment.
- Why this job: Make a real impact in AI by developing new capabilities for Language Models.
- Qualifications: Strong Python skills and experience with machine learning and Large Language Models.
We are looking for Research Engineers to help us redesign how Language Models interact 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 Language Models! 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
- Extending traditional ideas like RAG into heterogeneous data types (image, tables, relational data, etc.)
You may be a good fit if you:
- Have significant Python programming experience
- 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:
- Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, indexing, ranking, query understanding, and distributed data processing
- Conducting research to advance search quality and knowledge base systems
- Understanding Retrieval Augmented Generation (RAG) and its limitations
- Collaborating with product teams to quickly prototype and deliver innovative solutions
The expected salary range for this position is: Annual Salary: $280,000—$485,000 USD
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.
- US visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate; operations roles are especially difficult to support. But if we make you an offer, we will make every effort to get you into the United States, 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.
Compensation and Benefits
Anthropic’s compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates.
Equity - For eligible roles, equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance.
US Benefits - The following benefits are for our US-based employees:
- Optional equity donation matching.
- Comprehensive health, dental, and vision insurance for you and all your dependents.
- 401(k) plan with 4% matching.
- 22 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
- Stipends for education, home office improvements, commuting, and wellness.
- Fertility benefits via Carrot.
- Daily lunches and snacks in our office.
- Relocation support for those moving to the Bay Area.
UK Benefits - The following benefits are for our UK-based employees:
- Optional equity donation matching.
- Private health, dental, and vision insurance for you and your dependents.
- Pension contribution (matching 4% of your salary).
- 21 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
- Health cash plan.
- Life insurance and income protection.
- Daily lunches and snacks in our office.
Research Engineer, Knowledge Bases employer: Anthropic
At Anthropic, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among world-class ML researchers. Our commitment to employee growth is reflected in our generous benefits package, including unlimited PTO, comprehensive health coverage, and equity opportunities, all designed to support your well-being and professional development. Located in the vibrant Bay Area, we provide a stimulating environment where you can make a meaningful impact on the future of AI while enjoying a flexible hybrid work policy.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer, Knowledge Bases
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and machine learning. This is your chance to demonstrate how you can design new architectures and work with language models.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of RAG and other relevant concepts. Practice explaining your past experiences and how they relate to the role. We want to see your passion for the societal impacts of AI!
✨Tip Number 4
Don’t hesitate to apply through our website, even if you don’t tick every box. We value diverse perspectives and believe that strong candidates come in all shapes and sizes. Your unique background could be just what we need!
We think you need these skills to ace Research Engineer, Knowledge Bases
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python programming experience and any machine learning research you've done. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application:Take a moment to customise your application for this specific role. Mention how your past experiences relate to designing new information architectures and working with language models. It’ll make you stand out!
Be Yourself:We value authenticity! Don’t worry if you don’t meet every single qualification. If you’re passionate about the work we do and believe you can contribute, just go for it. We want to hear your unique perspective.
Apply Through Our Website:For the best chance of getting noticed, apply directly through our website. It’s the easiest way for us to keep track of your application and ensure it gets into the right hands!
How to prepare for a job interview at Anthropic
✨Know Your Stuff
Make sure you brush up on your Python programming and machine learning concepts. Be ready to discuss your experience with large language models and how you've applied them in past projects. This will show that you're not just familiar with the theory but have practical knowledge too.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems, especially in designing information architectures or improving search quality. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to follow your thought process.
✨Emphasise Collaboration
Since this role involves a lot of pair programming and collaboration with researchers, be ready to talk about your teamwork experiences. Share specific instances where you worked closely with others to achieve a common goal, highlighting your flexibility and willingness to pick up slack.
✨Understand the Bigger Picture
Familiarise yourself with the societal impacts of AI and language models. Be prepared to discuss your thoughts on ethical considerations and how they relate to the work you'll be doing. This shows that you care about more than just the technical aspects and are invested in the implications of your work.