Staff AI Scientist
On-sitePalo Alto, California, United States
Job Summary
Design and implement AI systems handling complex workflows, including multi-step reasoning, planning, and decision making under real operational constraints. Lead systematic experimentation across prompts, agents, and model variants, defining evaluation strategies for task success, robustness, and hallucination analysis. Fine-tune and adapt small and medium-sized foundation models using techniques like PEFT, SFT, and reinforcement learning to balance performance, latency, and cost for enterprise-grade workloads. Own bounded, end-to-end AI workflows from problem framing through deployment, partnering with engineering teams on integration and lifecycle management. Mentor junior scientists on experimentation methodology and influence roadmap direction through evidence-backed recommendations.
Required Qualifications
- MS or PhD in Computer Science, Machine Learning, Operations Research, Statistics, or related fields
- 5+ years designing, building and iterating on ML systems
- hands‐on experience using frontier models and open-source models
- Experience in translating business impact into quantitative metrics
- designing experiments and statistical analysis of results
- Experience in working with cross-functional teams to deliver ML capabilities in customer-facing products
- maintaining ML quality
- Strong communication skills, verbal and written
Desired Qualifications
- Strong experience in model training, building autonomous agentic systems and agentic workflows, and rigorous evaluation of agentic systems
- Demonstrated track record of excellence (e.g., publications at top-tier peer-reviewed conferences or journals) or significant product impact with highly technical solutions, and desire to grow
- Experience at fast-growing companies or startups, or working in an agile environment
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