Staff AI Scientist (AI Foundations)

Location: Mountain View, California, United States

Base pay: $209,500–$283,500 per year, plus cash bonus, equity rewards, and benefits.

Company

hirify.global is a global financial technology platform serving consumers and small businesses through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Design, develop, and deploy production-grade GenAI and machine learning solutions.
• Architect LLM evaluation tooling, including leaderboards, benchmark suites, and experimentation pipelines.
• Define LLMOps practices for model development, deployment, monitoring, retraining, cost optimization, and reliability.
• Build responsible AI controls addressing fairness, transparency, safety, hallucinations, bias, and privacy risks.
• Partner with product, engineering, data science, and design teams to deliver AI capabilities aligned with customer and business outcomes.
• Evaluate emerging techniques such as RAG, prompt chaining, orchestration, and MCP, while mentoring scientists and communicating strategy to technical and non-technical leaders.

Requirements

• Bachelor’s, Master’s, or PhD in computer science or a related field, or equivalent practical experience.
• 8+ years of applied ML/AI experience delivering scalable, production-grade AI systems.
• Hands-on experience with agentic AI workflows and Python frameworks such as LangGraph, LlamaIndex, or LangChain, including memory management, orchestration, semantic search, tool use, and contextual reasoning.
• Expertise in GenAI system design, LLM integration, RAG, and evaluation or observability frameworks for LLMs or AI agents.
• Experience designing APIs and deploying ML services in AWS or GCP cloud-native environments with containerization and CI/CD.
• Strong cross-functional collaboration, communication, product hirify.globalion, and strategic influence skills.

Nice to have

• Familiarity with the Model Context Protocol and connecting AI agents with tools and external data.

Culture & Benefits

• Collaboration with ML engineers, data scientists, product managers, and architects.
• Mentorship and participation in an inclusive AI science community focused on innovation and technical excellence.
• Competitive pay-for-performance compensation.
• Cash bonus, equity rewards, and employee benefits.
• Regular compensation comparisons across ethnicity and gender categories to support fair pay.