Description:

Sentient is pioneering the decentralized artificial general intelligence (AGI) frontier, aiming to democratize AI development.
The company is building a platform that empowers communities to collaboratively train and control AI models in an open and accessible ecosystem.
The role involves working part-time or full-time with the core Sentient Research team.
Responsibilities include conducting generative AI research, designing new agent architectures, and evaluating experiments to improve LLMs.
The intern will execute data engineering tasks for LLM pre-training and fine-tuning, and integrate models with multi-modal capabilities.
The position requires reading and evaluating conference papers on generative AI and knowledge retrieval.
The intern will replicate and integrate theoretical approaches from research papers into real products and set up fine-tuning and evaluation pipelines on cloud platforms.
Managing AI workload compute resources and monitoring experiments is also part of the role.

Requirements:

Candidates must have hands-on experience in generative AI research and/or engineering, either in industry or through academic work during their Bachelor’s, Master’s, or PhD degree, with corresponding published work.
Demonstrated expertise in deep learning and transformer models is required.
Mastery of Python, including PyTorch, numpy, and agentic frameworks, is essential for building AI workflows and fine-tuning models.
A strong foundation in data structures, algorithms, and software engineering principles is necessary.
Familiarity with methods for training LLMs, such as distillation and supervised fine-tuning, is expected.
Excellent problem-solving and analytical skills, along with a proactive approach to challenges, are crucial.

The position offers a competitive salary.
Employees enjoy a flexible PTO and work-from-home policy.
The company provides access to top-of-the-line engineers and technology.
There is an opportunity to shape the direction of a pioneering open AI platform.