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AI Engineer, Multimodal LLMs
AI Engineer, Multimodal LLMsEloquent AI • San Francisco, California, United States
AI Engineer, Multimodal LLMs

AI Engineer, Multimodal LLMs

Eloquent AI • San Francisco, California, United States
[job_card.30_days_ago]
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  • [job_card.full_time]
[job_card.job_description]

Meet 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 far beyond chat : it sees, reads, clicks, types, and makes decisions—transforming how work gets done in regulated, high-stakes environments.

We’re already powering some of the world’s leading financial institutions and insurers, fundamentally changing how millions of people manage their finances every day. From automating compliance reviews to handling customer operations, our Operators are quietly replacing repetitive, manual tasks with intelligent, end-to-end execution.

Headquartered in San Francisco with a global footprint, Eloquent AI is a fast-growing company backed by top-tier investors. Join us to work alongside world-class talent in AI, engineering, and product as we redefine the future of financial services.

Your Role

As an AI Engineer at Eloquent AI, you will be at the forefront of building, deploying, and optimizing enterprise-grade AI agents that handle high-stakes conversations. You’ll work directly with software engineers, deep learning experts and AI researchers to design intelligent agents that understand, take action, and deliver real business impact.

This role requires a mix of software development, AI integration, and problem-solving skills, with the ability to customize, optimize, and scale AI models for real-world enterprise applications. If you're passionate about LLMs, conversational AI, and solving last-mile AI adoption challenges, this role is for you.

You will :

Build, deploy, and optimize AI agents that engage in enterprise-grade conversations.

Design & develop next-gen multimodal LLM architectures (LLMs, speech, vision, reinforcement learning)

Explore optimal trade-offs between model quality and efficiency when translating research into practical solutions

​Refine training paradigms for real-world applications

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 or large computer vision models, or 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 to improve AI agents.

Strong problem-solving skills and the ability to work closely with customers to refine AI solutions.

Solid mathematical foundation of machine learning and deep learning techniques

Bonus Points If…

You have experience with prompt engineering, parameter-efficient fine-tuning (PEFT), retrieval-augmented generation (RAG), reinforcement learning for LLMs.

You’ve published AI research in top tier AI conferences like : NeurIPS, ACL, SIGIR, ICML and ICLR.

You’ve contributed to open-source NLP projects.

You’ve worked in a fast-paced startup environment and thrive in rapid iteration cycles.

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