Staff AI Scientist

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 infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data.   As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.    Job Description: About the role 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!   Responsibilities AI System Design & Implementation   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.   Experimentation & Evaluation   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   decision making .   Model Optimization & SLMs   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.   Applied   EndtoEnd   Delivery   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.   Technical Leadership   Act as a technical reference point for agentic AI best practices across the team.   Mentor junior scientists on experimentation   methodology , evaluation design, and practical GenAI system development.   Influence roadmap and technical direction through  evidencebacked   recommendations.   We're   Eager to Work with   Those who want to join our mission to democratize AI to more business users.   Individuals with an unwavering customer focus, committed to crafting experiences that delight.   Those who embrace excellence and consistently deliver top-tier work.   Innovators who thrive on creative thinking and daring to tread new paths.   Owners at heart, ready to take responsibility and drive results.   Individuals of the highest integrity, who foster trust and honesty.   Minimum Qualifications   Education: MS or PhD in Computer Science, Machine Learning, Operations Research, Statistics, or related fields   Applied ML / GenAI Experience: 5+ 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   Strong communication   skills, verbal and written   Preferred 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   Benefits : In addition to competitive base pay, this position also includes an annual incentive opportunity based on target achievement,  pre-IPO stock options, benefits including medical, dental, vision, 401(k) with a match, and more, plus generous paid time off, paid holidays, paid day off for your birthday and other