AI Engineer, Multimodal LLMs
Eloquentai · San Francisco
About this role
## AI Engineer, Multimodal LLMs **About Eloquent AI** At Eloquent AI, we’re building the next generation of AI Operators—multimodal, autonomous systems that execute complex workflows across fragmented tools with human-level precision. Our technology goes beyond chat: it can **see, read, click, type, and make decisions**, transforming how work gets done in **regulated, high-stakes environments**. We power leading financial institutions and insurers, automating tasks like **compliance reviews** and **customer operations** with intelligent, end-to-end execution. Headquartered in **San Francisco** with a global footprint, we’re a fast-growing team backed by top-tier investors. --- ## Your Role As an **AI Engineer**, you’ll build, deploy, and optimize **enterprise-grade AI agents** that handle high-stakes conversations. You’ll work closely with software engineers, deep learning experts, and AI researchers to design agents that **understand, take action, and deliver real business impact**. This role blends **software development**, **AI integration**, and **problem-solving**, with the ability to customize, optimize, and scale AI models for real-world enterprise applications. --- ## What You’ll Do - Build, deploy, and optimize AI agents for enterprise-grade conversations - Design & develop next-gen **multimodal LLM architectures** (LLMs, speech, vision, reinforcement learning) - Explore trade-offs between **model quality and efficiency** when moving from research to production - Refine training paradigms for real-world applications - Integrate AI agents with enterprise systems via **APIs, databases, and automation tools** - Experiment rapidly to improve interaction quality, response quality, and automation capabilities - Collaborate with cross-functional teams (engineering, research, product) to shape the roadmap - Monitor and improve agent performance using **user simulations and evaluations** --- ## Requirements - **3+ years** of experience in software development, AI engineering, or NLP in a production environment - Strong proficiency in **Python**, including experience with **PyTorch** and/or **TensorFlow** - Experience with **LLMs** or large computer vision / generative AI 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 - Strong problem-solving skills and ability to work closely with customers to refine solutions - Solid mathematical foundation in machine learning and deep learning --- ## Bonus Points If… - Experience with **prompt engineering**, **PEFT (parameter-efficient fine-tuning)**, **RAG (retrieval-augmented generation)**, and/or **RL for LLMs** - Published AI research in top-tier conferences such as **NeurIPS, ACL, SIGIR, ICML, ICLR** - Contributed to open-source NLP projects - Thrived in a fast-paced startup environment with rapid iteration cycles
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