Senior Staff AI Research Scientist (AI)

Location: Mountain View, California, or San Diego, California

Base pay: $226,000–$306,000 in Mountain View; $211,500–$286,000 in San Diego.

Company

Global financial technology platform delivering products for tax preparation, accounting, personal finance, and small business management.

What you will do

• Define the research agenda and identify high-impact AI/ML problems.
• Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and LLM-based reasoning.
• Lead research programs across multiple concurrent workstreams and set technical direction.
• Publish findings in top-tier conferences and journals and represent research contributions externally.
• Collaborate with product and platform teams to translate research into platform and customer-facing AI capabilities.
• Mentor junior researchers and establish academic and external research collaborations.

Requirements

• PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field.
• 8+ years of post-PhD AI/ML research experience with strong top-tier publication record.
• Deep expertise in at least one listed AI research area and strong fundamentals in deep learning, optimization, and statistical machine learning.
• Experience leading research projects and providing technical direction across multiple projects and researchers.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Strong communication skills and experience translating research into real-world industry impact.

Nice to have

• Experience as a research tech lead.
• Active participation in the research community through program committees, reviewing, or workshops.
• Familiarity with tax preparation, accounting, personal finance, or small business management.

Culture & Benefits

• Cash bonus, equity rewards, and employee benefits are included in the compensation package.
• Opportunities to contribute through reading groups, seminars, and internal knowledge sharing.
• Work includes collaboration across product, platform, academic, and external research communities.