Staff Applied AI Researcher

Location: Dublin, CA (HQ), United States

Company

hirify.global develops GenAI infrastructure for regulated enterprises, combining domain-specific models, autonomous agentic reasoning, model evaluation, and multimodal understanding.

What you will do

• Set technical direction for agentic reasoning systems and runtime intelligence across ModelMesh, including orchestration, decision policies, verification, and runtime quality standards.
• Design agentic platforms and orchestration primitives that enable researchers and engineers to run large-scale experimentation, evaluation, and production integration.
• Advance learned components for routing, verification, confidence estimation, reward modeling, and policy selection through parallel research pipelines.
• Develop methodologies that combine perception, retrieval, reasoning, knowledge graphs, domain models, and external tools into reliable agentic workflows.
• Lead reliability research for regulated environments, including failure detection, self-checking, red-teaming, stress testing, auditability, and recovery.
• Define continuous evaluation methods for task success, decision quality, robustness, traceability, and regression detection while mentoring researchers.

Requirements

• PhD or MSc in Computer Science, Machine Learning, AI, Robotics, or a related field.
• 8+ years of AI/ML research experience with production impact, including 3+ years building LLM-based or autonomous AI systems.
• Hands-on experience in at least two areas including multi-agent coordination, planning under uncertainty, sequential decision-making, probabilistic inference, model routing, or tool-using agents.
• Experience designing evaluation frameworks for autonomous systems, including decision quality, distribution shift, compounding errors, and failure recovery.
• Experience designing and operating multi-model research systems in production or near-production environments.
• Strong Python and software architecture skills, plus experience setting technical direction and mentoring researchers.

Nice to have

• Experience with dynamic routing, verification loops, probabilistic gating, Bayesian inference, control theory, or formal verification.
• Reliability engineering experience for autonomous AI in regulated environments, including observability, safety constraints, graceful degradation, and audit trails.
• Experience integrating retrieval, knowledge graphs, domain models, and external APIs into production agent systems.
• Strong publication record and experience taking reasoning or agent systems from prototype to enterprise production.
• Domain familiarity with energy, semiconductors, finance, aerospace, telecom, or supply chain.

Culture & Benefits

• Emphasis on humility, evidence-based technical direction, and letting the best idea win.
• Focus on customer and platform outcomes alongside research quality.
• Responsibility for building reliable, trustworthy, auditable, and fair autonomous systems.
• Investment in researcher growth, clarity, mentoring, and technical rigor.