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 – Machine Learning (Early Career) **Role Summary** Design, build, and maintain end‑to‑end machine‑learning pipelines that fuse structured and unstructured data to power AI‑driven personal digital twins. Work beside product and engineering teams to transition prototypes into production‑grade systems, focusing on large language model (LLM) integration, retrieval‑augmented generation (RAG), and voice technologies. **Expectations** - Deliver reliable, scalable ML solutions within a fast‑paced startup environment. - Iterate quickly from prototype to deployment while maintaining high code quality. - Communicate progress and technical decisions clearly to cross‑functional stakeholders. - Embrace a mission‑driven culture and contribute to product innovation. **Key Responsibilities** - Architect and implement ML workflows combining structured datasets and conversational logs. - Experiment with and fine‑tune LLMs (OpenAI, Anthropic, etc.) and retrieval systems. - Build and optimize vector‑database backends for RAG pipelines. - Integrate voice cloning, speech synthesis, or related audio ML components as required. - Deploy models to cloud platforms (AWS, Azure, GCP) and manage associated infrastructure. - Collaborate with product, data, and software teams to align AI features with user needs. - Document design, best practices, and operational procedures for sustainment. **Required Skills** - Proficiency in Python and ML libraries (PyTorch, TensorFlow, Hugging Face). - Hands‑on experience with large‑scale language models, prompt engineering, and RAG pipelines. - Familiarity with vector databases (Pinecone, Weaviate, Milvus, etc.) and similarity search. - Experience deploying ML models on cloud platforms (AWS SageMaker, Azure ML, GCP Vertex). - Strong data‑engineering mindset: ETL, feature pipelines, data versioning. - Knowledge of voice/audio ML workflows (speech synthesis, voice cloning) is a plus. - Excellent problem‑solving, debugging, and communication skills. - Comfortable working in an Agile/Scrum environment. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or related field; Master’s is preferred. - Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, GCP Professional ML Engineer, Azure AI Engineer Associate) are advantageous but not mandatory. ---

Los altos, United states

On site

15-01-2026