Senior AI Engineer

AI Futures; München; Vor Ort; EUR 110.000 - 160.000; Vollzeit

Zusammenfassung

A fast-growing AI scale-up in Munich is looking for a Senior AI Engineer to work on their LLM stack, engage with teams to create scalable solutions, and lead the development of LLMs. The ideal candidate will have a deep understanding of LLMs, strong ML and NLP knowledge, and excellent English communication skills. This role offers a career-defining opportunity to deliver impactful AI solutions as the company enters hyper-scale mode.

Qualifikationen

• Deep understanding of LLMs and their uses in commercial settings.
• Strong knowledge of ML and NLP techniques.
• Extensive experience including ML deployment and MLOps.
• Data engineering experience is advantageous.
• Strong English communication.

Aufgaben

• Work directly on the LLM stack that is central to the company's core product.
• Engage with cross-functional teams to deliver robust solutions.
• Lead development of LLMs including training and fine-tuning.
• Prototype new solutions and ideas to improve LLM capabilities.
• Create LLM-driven products and features to manage complex NLP tasks.

Kenntnisse

Understanding of LLMs

ML and NLP techniques

Communication skills in English

MLOps experience

Data engineering

English fluency

Jobbeschreibung

AI Futures are engaged on the search for a Senior AI Engineer for one of the most exciting and fastest growing scale-ups in Germany.

As part of their ongoing growth, AI Futures are searching for several Staff or Senior level AI Engineers to join their AI team. This is an opportunity to be part of the core service offering of an AI company as they enter hyper-scale mode and is a career-defining move for the right candidate.

Responsibilities:

• Work directly on the LLM stack that is central to the company's core product
• Engage with cross-functional teams to deliver robust and scalable solutions to deliver impactful business outcomes
• Lead development of LLMs including training and fine-tuning
• Prototype new solutions and ideas to improve LLM capabilities
• Create LLM-driven products and features to manage complex NLP tasks

Requirements:

• Deep understanding of LLMs and their uses in commercial settings
• Strong knowledge of ML and NLP techniques
• Extensive end-to-end experience including ML deployment and MLOps particularly with regards to LLMs and NLP
• Experience with data engineering tasks highly advantageous
• Strong communication skills in English

In return, you will have the opportunity to deliver end-to-end AI solutions with a tangible impact for customers whilst gaining the experience of working in a company as they enter hyper-scale mode.