Senior AI Scientist

Overview

Uniphore is building the world’s best‑in‑class Business AI platform to enable business users to leverage advances of artificial intelligence to solve problems in their specific business processes. The role is located in Palo Alto, CA, and focuses on building the agent learning platform and SLM AI flywheel that powers our Business AI cloud.

• Agentic AI Architecture & Orchestration
  • Design and implement production‑grade agentic systems capable of multi‑step reasoning, planning, tool use, and decision‑making under real operational constraints (latency, cost, safety).
  • Own the orchestration layer of the agent learning platform: agent memory, inter‑agent communication, failure recovery, and reliability patterns at enterprise scale.
  • Translate abstract product requirements into reliable AI behaviours and set the architectural standards the team builds against.
• Agent Learning & SLM Optimization
  • Own the closed‑loop learning pipeline: capturing production signal from deployed agents, triggering fine‑tuning cycles, and gating model promotion into production.
  • Fine‑tune and adapt small and medium‑sized foundation models using techniques such as PEFT, SFT, distillation, and reinforcement learning (RLHF, DPO).
  • Drive model selection decisions (SLMs vs. larger models) based on use‑case requirements, latency SLAs, and empirical evidence.
• Evaluation & Experimentation
  • Define and build evaluation strategy for agentic systems: task success metrics, trajectory evaluation, hallucination analysis, and regression detection across the learning flywheel.
  • Develop offline and online evaluation loops—including LLM‑as‑judge frameworks—that guide rapid iteration and provide the ground truth signal the flywheel depends on.
  • Lead systematic experimentation across prompts, agent configurations, model variants, and tool integrations.
• End‑to‑End Delivery & Production Ownership
  • Own bounded, end‑to‑end ML workflows from problem framing through deployment, monitoring, and lifecycle management.
  • Partner with engineering on integration, observability, and production readiness—without acting as a full‑time infrastructure owner.
  • Identify systemic gaps across the ML stack (accuracy, latency, cost, reliability) and lead the work to close them.
• Technical Leadership
  • Act as the technical reference point for agentic AI and SLM best practices across the team.
  • Drive cross‑functional alignment with product and engineering through evidence‑backed technical recommendations that influence the roadmap.
  • Mentor senior and mid‑level engineers on experimentation methodology, evaluation design, and production ML system development.

• MS or PhD in Computer Science, Machine Learning, Statistics, or a related field.
• 8+ years designing, building, and operating production ML systems, with hands‑on experience with frontier and open‑source models.
• Proven track record owning agentic AI systems or closed‑loop model improvement pipelines in production—beyond prototype quality.
• Deep experience with LLM or SLM fine‑tuning: SFT, RLHF/DPO, data curation, and rigorous evaluation design.
• Experience translating business impact into quantitative metrics and designing statistically sound experiments.
• Track record of influencing technical decisions beyond your immediate team—through design docs, architectural reviews, or cross‑functional alignment.
• Strong communication skills, verbal and written, with the ability to present technical strategy to non‑technical stakeholders.

• Experience designing evaluation frameworks for agentic systems (trajectory evaluation, task success, robustness benchmarks).
• Demonstrated influence at an organizational or platform level: architectural standards or platform decisions that multiple teams built against.
• Familiarity with agentic orchestration frameworks (e.g., Lang Graph).
• Background in enterprise NLP, conversational AI, or contact center / CX domains.
• Publications at top‑tier peer‑reviewed venues or significant open‑source contributions in relevant areas.
• Experience at fast‑growing companies or in agile, high‑ownership engineering environments.

Uniphore is an equal‑opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.