Research Engineer, Applied AI

kapa.ai; Österreich; On-site; EUR 85,844 - 128,766; Full time

Job summary

Join a leading company to innovate in the AI sector as a Research Engineer, Applied AI. Working with a dedicated team, you'll tackle complex technical challenges while contributing to cutting-edge projects in machine learning and natural language processing. Ideal candidates have a background in advanced computer science and hands-on experience with AI technologies.

Qualifications

• Detailed understanding of machine learning, deep learning, and NLP.
• Hands-on experience training and deploying large language models.
• Experience with vector databases and search retrieval.

Responsibilities

• Work directly with the founding team on AI advancements.
• Research state-of-the-art retrieval and search techniques.
• Deploy machine learning models as part of RAG.

Skills

Machine Learning

Deep Learning

Natural Language Processing

Information Retrieval

Education

Master's/PhD in Computer Science, Machine Learning, Mathematics, Statistics

Job description

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Join to apply for the Research Engineer, Applied AI role at kapa.ai

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This range is provided by kapa.ai. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$100,000.00/yr - $150,000.00/yr

As a research engineer you will work on improving kapa’s ability to answer harder and harder technical questions. Check out Docker’s documentation for a live example of what kapa is (look for the “Ask AI” button).

In This Role, You Will

• Work directly with the founding team and our software engineers.
• Work on and do research in state-of-the-art retrieval and search techniques.
• Work on and deploy machine learning models as part of RAG.
• Continuously improve our quality evaluation frameworks to enable robust iteration.
• Keep up with the latest developments in the space and see how they can be applied.
• Design and run experiments.
  
  

In addition to the founding team, you'll have support from a number of leading academics in the field that are all close advisors (incl. Douwe Kiela, author of the original RAG paper).

You May Be a Good Fit If You Have

• A Master's/ PhD degree in Computer Science, Machine Learning, Mathematics, Statistics or a related field.
• A detailed understanding of machine learning, deep learning (including LLMs) and natural language processing.
• Hands-on experience in training, fine-tuning and deploying large language models.
• Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases.
• Significant experience building evaluation systems for LLMs or search.
• Familiarity with various information retrieval techniques, such as lexical search and dense vector search.
• The ability to work effectively in a fast in a environment where things are sometimes loosely defined.
• Want to learn more about machine learning research.
• This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to kapa.ai, please reach out.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development

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