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Salary: USD 200,000 - 260,000 / annual
Uare.ai is building Human-First AI—personalized AI models trained on individual users rather than general models. The company's Human Life Model (HLM) captures seven dimensions of who someone is, with data remaining private to each person. Founded by Rob LoCascio (former CEO of LivePerson) and backed by $10.3M from Mayfield and Boldstart Ventures, Uare.ai is now deploying into U.S. defense programs.
In this role, you will be responsible for making the HLM run reliably and performantly on Azure OpenAI inside a Department of Defense War Impact Level 5 (IL5) boundary, proving it performs as well in the government environment as it does commercially.
Key responsibilities:
- Stand up and tune Azure OpenAI and Azure AI Speech in Azure Government for quality, latency, and cost optimization
- Port RAG and HLM pipelines onto Azure Government services, ensuring nothing leaves the IL5 boundary
- Build and run evaluations for accuracy, grounding, and refusals; report results to customers
- Own model provenance: track model versions, prompts, approved images, and data lineage for Authority to Operate (ATO) documentation
- Implement Voice Capture on Azure AI Speech within IL5
- Build access control and audit logging in collaboration with the full-stack engineering team
You will report to the CTO and work in-person 5 days a week across San Francisco and Los Altos offices, with occasional travel to customer sites.
Requirements:
- U.S. citizenship (required for government contracts)
- Hands-on experience deploying ML or LLM systems in a DoD IL5 environment (Azure Government preferred)
- 7+ years in ML or applied AI, owning models that serve real traffic
- Deep experience with Azure OpenAI or similar hosted models, RAG, vector search (e.g., Azure AI Search), and evaluation frameworks
- Comfort working in disconnected or tightly restricted environments where standard package management is unavailable
- Ability to pass a U.S. government background investigation; active clearance is a plus
Bonus qualifications:
- Speech and audio ML experience (ASR, voice synthesis)
- Fine-tuning models on Azure OpenAI or Azure Machine Learning
- Iron Bank / Platform One container pipelines
