Senior Staff AI Scientist

Uniphore•Palo Alto, CA

22h•Onsite

About The Position

Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments. Uniphore is building the world’s best-in-class Business AI platform to enable business users to leverage the advances of artificial intelligence to solve problems in their specific business processes. Uniphore provides a composable, sovereign, and secure solution to business users, and drives AI adoption in organizations with innovative solutions to building, serving, and optimizing these AI solutions. Location: Palo Alto, CA You will be working on developing new foundational machine learning technology behind a category-defining product – Business AI will democratize the benefits of cutting-edge machine intelligence at scale to more customers. If you are ready to take on the challenge of building the foundation model that enables a wide suite of capabilities around AI agent optimization, training of small and efficient foundation models, human-AI interaction, and agentic evaluation, etc., come join us!

Requirements

MS or PhD in Computer Science, Machine Learning, Operations Research, Statistics, or related fields
8+ years designing, building and iterating on ML systems, with hands‑on experience using frontier models and open-source models.
Experience in translating business impact into quantitative metrics and designing experiments and statistical analysis of results
Experience in working with cross-functional teams to deliver ML capabilities in customer-facing products and maintaining ML quality
Experience in leading strategic AI initiatives and derisking applied research execution
Strong communication skills, verbal and written

Nice To Haves

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

Responsibilities

Design and implement AI systems capable of handling complex workflows, including multi-step reasoning, planning, and decision making.
Explore and apply various orchestration patterns and architectures to solve business problems effectively.
Translate abstract requirements into reliable AI behaviors under real operational constraints such as latency, cost, and safety.
Lead systematic experimentation across prompts, agents, model variants, and tool configurations.
Define and implement evaluation strategies for agentic systems, including task success, robustness, failure recovery, and hallucination analysis.
Develop lightweight benchmarks, simulations, and offline/online evaluation loops to guide rapid iteration and decisionmaking.
Finetune and adapt small and medium-sized foundation models using techniques such as PEFT, SFT, distillation, and reinforcement learning.
Balance performance, latency, and cost for enterprisegrade workloads.
Contribute to model selection decisions (SLMs vs. larger models) based on usecase requirements and empirical evidence.
Own bounded, endtoend AI workflows from problem framing through deployment where this accelerates impact.
Partner with engineering teams on integration, monitoring, and lifecycle management.
Contribute to production readiness without acting as a fulltime platform or infrastructure owner.
Act as the subject matter expert in strategic domains within the team.
Help identify and drive strategic technical directions crucial for business growth.
Mentor junior scientists on experimentation methodology, evaluation design, and practical GenAI system development.
Influence roadmap and technical direction through evidencebacked recommendations.