Staff AI Scientist

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

Hiring Pay Range

$192,500 - $240,600

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 paid leave policies to support employees through all phases of life.