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:
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 decisionmaking.
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 Range:
The specific rate will depend on the successful candidate's qualifications and prior experience.
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.
Location preference:
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.
For more information on how Uniphore uses AI to unify—and humanize—every enterprise experience, please visit www.uniphore.com.
Top Skills
What We Do
The Uniphore Business AI Cloud spans agents, models, knowledge, and data, combining the simplicity of consumer AI with the rigor, security, and scalability the enterprise demands. Business users can harness AI effortlessly and deliver outcomes immediately, while CIOs gain the foundation to build powerful AI applications embedded into workflows and trained on enterprise data. Built for the Enterprise, backed by AI Leaders Backed by NVIDIA, AMD, Snowflake, and Databricks, Uniphore brings a unique combination of capital and strategic alignment — validating its position as the definitive Business AI leader. Recent acquisitions of ActionIQ, Infoworks, Orby AI, and Autonom8 further cement Uniphore's AI talent depth and accelerate outcomes for clients. A Complete, Composable Platform Uniphore is designed to be: Sovereign — run on any public cloud, private cloud or on-premises with full control over your data and AI models. Composable — choose your layer, model, or component—vector DBs, knowledge graphs, data compute, and beyond. Secure — embedded guardrails, observability, and AI security ensure trusted, compliant, and enterprise-grade protection. Trusted at Scale Over 2,000 global businesses — including many of the Fortune 500 — rely on Uniphore every day to drive growth, improve efficiency, and deliver personalized customer experiences. Customers include leaders across industries, like Skechers, LastPass, Atlassian, HP, Allstate, Sony, and more. Industry Recognition Named to Inc.'s Best in Business List Listed on the Deloitte Technology Fast 500 Recognized in reports by Gartner, Forrester, and IDC From Pilot to Production Through strategic collaborations with industry leaders like KPMG, Cognizant, Rackspace, Databricks and Snowflake, Uniphore helps organizations move beyond experimental AI pilots to production-grade deployment — operationalizing AI agents across internal and client-facing workflows at scale.
