Responsibilities
- Build, deploy, and optimize AI agents that engage in enterprise-grade conversations.
- Work with customers to understand business needs, assess AI capabilities, and implement tailored solutions.
- Train and fine-tune LLMs for improved accuracy and efficiency.
- Integrate AI agents with enterprise systems via APIs, databases, and automation tools.
- Experiment rapidly to improve AI-driven interactions, response quality, and automation capabilities.
- Collaborate with cross-functional teams (engineering, research, and product) to shape Eloquent AI’s roadmap.
- Monitor and improve agents’ performance via user simulations and evaluations.
Requirements
- 3+ years of experience in software development, AI engineering, or NLP in a production environment.
- Strong proficiency in Python, with experience in frameworks like PyTorch and TensorFlow.
- Experience working with LLMs and NLP models, including fine-tuning and inference optimization.
- Familiarity with APIs, cloud infrastructure (AWS, GCP, or Azure), and enterprise integrations.
- Ability to prototype, experiment, and iterate quickly to improve AI agents.
- Strong problem-solving skills and the ability to work closely with customers to refine AI solutions.
Nice to Have
- Experience with prompt engineering, parameter-efficient fine-tuning (PEFT), retrieval-augmented generation (RAG), reinforcement learning for LLMs.
- Experience with frontend or backend development (React, Node.js, NestJS) to enhance AI-driven applications.
- Background in information retrieval or recommender systems, document question answering, or agent development.
- Published AI research in top tier AI conferences like: NeurIPS, ACL, SIGIR, ICML and ICLR.
- Contributed to open-source NLP projects.
- Worked in a fast-paced startup environment and thrive in rapid iteration cycles.
Work Arrangement
Remote (Worldwide) — San Francisco
