Eloquent AI Fellowship Program
12-week fellowship for PhD/MSc STEM graduates to gain hands-on experience in AI engineering, product development, and research. Fellows develop/deploy AI agents using LLMs/RAG, optimize models, and work on enterprise projects with mentorship from AI leaders.
About the job
Program Structure
- AI Engineering (6 weeks): Work on training, fine-tuning, and deploying AI agents that power enterprise-grade conversations. Gain hands-on experience in LLMs, RAG pipelines, prompt engineering, and inference optimization.
- AI Product Development (4 weeks): Collaborate with AI product teams to design, iterate, and integrate AI solutions into enterprise applications. Learn how to bridge the gap between cutting-edge AI research and real-world impact.
- Industry Applications & Capstone (2 weeks): Apply what you’ve learned in a real-world AI project, working with Eloquent AI’s product, engineering, and research teams to solve enterprise challenges.
Responsibilities
- Develop and deploy AI-powered agents, working with LLMs, RAG, and enterprise automation workflows.
- Gain hands-on experience in AI infrastructure, including LLMOps, MLOps, cloud deployment, and model optimization.
- Work on full-stack AI applications, collaborating with engineers and PMs to build scalable AI-driven products.
- Translate AI research into practical applications, integrating the latest advances in language models, embeddings, and retrieval techniques.
- Work directly with Eloquent AI’s leadership, learning from top AI engineers and product innovators.
Requirements
- Current or completed PhD or MSc degree in Computer Science, Engineering, Mathematics, Physics, or a related field.
- Strong mathematical foundation, particularly in statistics, linear algebra, and optimization techniques.
- Programming experience, ideally in Python, with familiarity in ML frameworks like PyTorch and TensorFlow.
- Interest in AI product development, data science, or machine learning engineering.
- Ability to work in a fast-paced, collaborative AI-driven environment.
Bonus Points If…
- Experience with LLMs, NLP, or Retrieval-Augmented Generation (RAG).
- Contributed to open-source AI projects or published research in AI/ML conferences (NeurIPS, ICML, ICLR, NLP, SIGIR, etc.).
- Hands-on experience with LLMOps, MLOps, cloud-based AI infrastructure, or AI deployment at scale.
- Experience in AI strategy, product management, or business applications of AI.
Skills
Python, PyTorch, TensorFlow, LLMs, RAG, MLOps, Llmops, NLP, Prompt Engineering, Cloud Deployment
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