Uare.ai, founded by Robert LoCascio (former CEO of LivePerson for 28 years), is an AI startup launched in May 2024 with a mission to empower people to do more with their memories. Uare.ai creates AI-driven personal digital twins, enabling users to preserve, share, and interact with their knowledge and stories in groundbreaking ways.
At its core is the proprietary Human Life Model (HLM), designed to process unstructured conversations and story data sets without training client data into traditional LLMs. Instead, Uare.ai leverages 3rd-party LLMs for conversations, with HLM providing structure and reasoning.
While initially focused on personal legacy and AI immortality, Uare.ai’ platform has broad B2C and B2B applications. The company has gained significant traction, featured in over 30 outlets including NBC, NPR, The New York Post, and CNET.
About the Role:
We are seeking a highly skilled Senior Machine Learning Engineer to join an early-stage, mission-driven startup that’s building cutting-edge AI-powered products for real-world human interaction. You will be responsible for designing and implementing scalable machine learning pipelines, integrating foundation models, and fine-tuning retrieval systems that deliver high-quality, context-aware responses.
What You’ll Do:
- Design and implement machine learning workflows that combine structured and unstructured data.
- Work with state-of-the-art language models and voice technologies.
- Build and optimize retrieval-augmented generation (RAG) systems.
- Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems.
- Help shape the future of AI-powered human interaction products.
What We’re Looking For:
- 4+ years of experience in machine learning, NLP, or AI.
- Strong experience with LLMs, RAG pipelines, vector databases, and prompt engineering.
- Hands-on experience with cloud-based AI platforms (AWS, Azure, or GCP).
- Familiarity with voice cloning, speech synthesis, or related audio ML workflows is a plus.
- Excited about building 0-to-1 products in a fast-moving environment.
