Research Engineer, Applied AI

kapa.ai; España; Presencial; EUR 85.000 - 129.000; Jornada completa

Descripción de la vacante

A technology company in Spain is seeking a Research Engineer, Applied AI to enhance AI capabilities. This role involves collaborating with the founding team, conducting research, and improving machine learning models. The ideal candidate should have a Master’s or PhD in a related field and experience in machine learning and NLP. This full-time position offers a salary range between $100,000 and $150,000 per year.

Formación

• Deep understanding of machine learning, deep learning (including LLMs), and NLP.
• Experience training, fine-tuning, and deploying large language models.
• The ability to work effectively in a fast-paced environment with sometimes loosely defined tasks.

Responsabilidades

• Work directly with the founding team and software engineers.
• Research state-of-the-art retrieval and search techniques.
• Deploy machine learning models as part of RAG.
• Improve quality evaluation frameworks for robust iteration.
• Stay updated with the latest developments and explore their applications.
• Design and run experiments.

Conocimientos

Machine learning

Deep learning

Natural language processing (NLP)

Information retrieval techniques

Educación

Master’s or PhD in Computer Science, Machine Learning, Mathematics, Statistics

Herramientas

Vector databases

Search indices

Descripción del empleo

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

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 increasingly complex 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.
• Research state-of-the-art retrieval and search techniques.
• Deploy machine learning models as part of RAG.
• Improve quality evaluation frameworks for robust iteration.
• Stay updated with the latest developments and explore their applications.
• Design and run experiments.

You will have support from leading academics in the field, including close advisors like Douwe Kiela, author of the original RAG paper.

You May Be a Good Fit If You Have

• A Master’s or PhD in Computer Science, Machine Learning, Mathematics, Statistics, or related fields.
• Deep understanding of machine learning, deep learning (including LLMs), and NLP.
• Experience training, fine-tuning, and deploying large language models.
• Experience with vector databases, search indices, or similar data stores.
• Experience building evaluation systems for LLMs or search.
• Knowledge of information retrieval techniques, such as lexical and dense vector search.
• The ability to work effectively in a fast-paced environment with sometimes loosely defined tasks.
• A desire to learn more about machine learning research.

Additional Information

• Seniority level : Entry level
• Employment type : Full-time
• Job function : Engineering and IT
• Industries : Software Development

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