Staff AI Machine Learning Engineer (Agentic AI)

Location: San Francisco, California, United States

Company

hirify.global develops AI-powered healthcare and clinical research workflows using large-scale healthcare data.

What you will do

• Lead the architecture and design of autonomous and multi-agent AI systems for healthcare workflows.
• Build production-grade agent infrastructure, including prompts, function tools, workflow graphs, MCP and A2A integrations, and adaptive agent lifecycles.
• Develop automated evaluation, benchmarking, regression, adversarial testing, observability, safety guardrails, and human-in-the-loop frameworks.
• Train, fine-tune, deploy, and optimize large-scale ML and LLM systems using healthcare datasets.
• Partner with researchers, clinicians, C-suite stakeholders, and cross-functional leaders to shape the agentic AI strategy and roadmap.
• Explore multimodal agents, advanced reasoning models, and interoperability protocols for transparent and compliant healthcare AI.

Requirements

• 7+ years of hands-on experience as a Machine Learning Engineer.
• Proven experience building and shipping production agentic AI systems in industry.
• Experience designing, optimizing, or integrating analytic engines or advanced analytics platforms at scale.
• Strong foundation in ML and AI, including NLP, LLMs, reinforcement learning, and planning or reasoning algorithms.
• Deep expertise with LangChain, LangGraph, MCP, A2A, Hugging Face, PyTorch, vector databases, semantic search, prompt engineering, and observability platforms.
• Experience building automated evaluation and testing pipelines for autonomous agents, including reliability, safety, factuality, cost, latency, and clinical utility metrics.

Nice to have

• Experience in healthcare or life sciences, including EHR or claims data and HIPAA, transparency, or reproducibility considerations.
• Publications or a strong record at leading AI/ML conferences and journals.
• Multi-cloud experience with AWS, Azure, or GCP.

Culture & Benefits

• Ownership from day one in a small, high-trust team with minimal organizational layers.
• Opportunity to build AI-powered workflows with direct impact on healthcare and clinical research.
• Work supporting drug development, health equity, and clinical research institutions.
• Series A company backed by top-tier investors with access to a data asset containing 200M+ patient records.