Uare.ai

About the Company

At Uare.ai (formerly Eternos), our mission is to help people do more with their memories by creating Personal AI - trained on your stories, experiences, values, knowledge, and voice. Unlike general AIs built to absorb everyone's knowledge, your Personal AI is designed to understand, reflect, and support you. Think of it as your second brain: it remembers what matters, helps you think more clearly, and keeps your perspective sharp. Our proprietary Human Life Model (HLM) powers this approach. The HLM processes first-person stories and unstructured conversational data in ways traditional large language models cannot. Importantly, we never train client data into 3rd-party LLMs - instead, they generate conversations, while the HLM ensures reasoning, structure, and continuity. Launched in May 2024, Uare.ai quickly gained attention with coverage in 30+ media outlets, including NBC, NPR, The New York Post, and CNET. While our first application taps into the cultural conversation around AI, memory, and legacy, our platform extends far beyond -- with powerful B2C and B2B applications across personal, professional, and enterprise use cases. Uare.ai Raises $10.3M from Boldstart Ventures & Mayfield

Listed Jobs

Company Name

Uare.ai

Job Title

Software Engineer (Early Career)

Job Description

Job title: Software Engineer (Early Career) Role Summary: Design, build, and scale machine‑learning pipelines for AI‑powered personal digital twin products. Integrate large language models, build retrieval‑augmented generation (RAG) systems, and optimize voice and speech synthesis workflows to deliver context‑aware responses. Expectations: Deliver production‑ready ML systems from prototype to deployment. Collaborate cross‑functionally with product and engineering teams. Build 0‑to‑1 products in a fast‑moving, mission‑driven startup environment. Key Responsibilities: - Develop end‑to‑end ML workflows combining structured and unstructured data. - Fine‑tune and deploy foundation language models and voice‑tech components. - Build, test, and optimize RAG pipelines using vector databases and prompt engineering. - Deploy models on cloud platforms (AWS, Azure, or GCP) and maintain scalability. - Collaborate with product, design, and software teams to iterate features and ensure reliability. Required Skills: - Strong foundation in machine learning, NLP, or AI. - Proficiency with large language models (LLMs) and RAG architecture. - Hands‑on experience with vector databases, prompt engineering, and retrieval systems. - Cloud AI platform experience (AWS, Azure, or GCP). - Knowledge of voice cloning, speech synthesis, or related audio ML workflows (plus). - Comfortable building 0‑to‑1 products and working in rapid‑iteration environments. Required Education & Certifications: - Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or related field (or equivalent practical experience).

Los altos, United states

On site

10-10-2025