AI Scientist Intern - (Internship, Masters or Phd)

Role Summary 

-You will be working with the fine tuning team on making state-of-the-art generative models.

-You will run autonomous work streams under the supervision of experienced scientists.

-The role is based in one of our offices in Paris, London, Zurich or Warsaw.

-Internship duration : 6 months. We will only consider candidates looking for end of studies internships (Master or Phd)

What you will do

-Explore state-of-the-art LLM algorithms for fine tuning LLMs, with the supervision of top level scientists.

-Assist in the design and implementation of machine learning models and algorithms.

-Conduct research on the latest advancements in natural language processing and LLMs.

-Contribute to the development and optimization of our LLM systems.

-Collaborate with cross-functional teams to integrate LLM technologies into various applications.

-Perform data analysis and visualization to support research and development efforts.

-Document research findings and contribute to technical reports and publications.

-Participate in team meetings and brainstorming sessions to share ideas and insights

-Currently doing a Master or PhD at a tier 1 engineering schools / Universities.

-High scientific understanding of the field of generative AI. 

-Broad knowledge of the field of AI, and specific knowledge or interest in fine-tuning and using language models for applications.

-Strong programming skills in Python, with experience in libraries such as TensorFlow, PyTorch, or similar.

-Familiarity with natural language processing techniques and machine learning algorithms.

-Design complex software and make them usable in production. 

-Navigate the full MLOps technical stack, with a focus on architecture development and model evaluation and usage. 

-Previous experience with LLMs or related technologies.

-Knowledge of deep learning frameworks and techniques..Experience with version control systems (e.g., Git) and linux shell environment.

-Have used complex HPC infrastructure with full autonomy.