What are the responsibilities and job description for the AI Scientist - Palo Alto (Internship (Phd) position at Mistral AI?
About Mistral
-At Mistral AI, we are a tight-knit, nimble team dedicated to bringing our cutting-edge AI technology to the world. Our mission is to make AI ubiquitous and open.
-We are creative, low-ego, team-spirited, and have been passionate about AI for years.
-We hire people that foster in competitive environments, because they find them more fun to work in.
-We hire passionate women and men from all over the world.
-Our teams are distributed between France, UK and USA
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 our Bay area offices
-Internship duration : 3 to 6 months. We will only consider candidates looking for end of studies internships (Phd)
Key Responsibilities
-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
Qualifications & profile
-Currently doing a Phd from 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.
Now, it would be ideal if you :
-Have experience in fine tuning LLMs.
-Have used complex HPC infrastructure with full autonomy.
Benefits
Attractive cash compensation
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