Uniphore Logo

Uniphore

Staff AI Scientist

Reposted 3 Months Ago
Be an Early Applicant
In-Office
Palo Alto, CA, USA
193K-241K Annually
Senior level
In-Office
Palo Alto, CA, USA
193K-241K Annually
Senior level
Design and implement agentic AI systems and workflows; lead experiments and evaluations for prompts, agents, and model variants; finetune and optimize small-to-medium foundation models; deliver end-to-end ML solutions into production; mentor junior scientists and influence technical roadmap.
The summary above was generated by AI

Uniphore is the Business AI company. Our sovereign, composable and secure AI platform connects enterprise data, fine-tunes AI models and deploys agentic AI across the enterprise. We empower every worker to boost productivity and help businesses grow faster, operate smarter and reduce costs. Trusted by more than 2,000 businesses globally, and recognized on the Deloitte Fast 500, Uniphore delivers on the promise of AI as a transformative force for business.


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 


 


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.


Location preference:

USA - CA - Palo Alto

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.

HQ

Uniphore Palo Alto, California, USA Office

1001 Page Mill Road, Palo Alto, CA, United States

Similar Jobs

2 Days Ago
In-Office
San Francisco, CA, USA
247K-339K Annually
Senior level
247K-339K Annually
Senior level
eCommerce • Fintech • Machine Learning • Retail
Lead the AI/ML vision and roadmap for retailer acquisition and paid marketing. Build models for spend allocation, bidding, lifetime value prediction, SEO and content opportunities, audience targeting, and landing-page optimization. Lead experiments measuring channel incrementality, translate models into growth decisions, and mentor Applied AI/ML Scientists and Analytics Engineers. Partner with marketing, product, engineering, and finance to drive measurable acquisition outcomes.
Top Skills: AeoArtificial IntelligenceLarge Language Models (Llms)Lifetime Value (Ltv) ModelingMachine LearningPerformance MaxRecommender SystemsSeo
2 Days Ago
Hybrid
San Francisco, CA, USA
234K-384K Annually
Senior level
234K-384K Annually
Senior level
Artificial Intelligence • Software • Generative AI
Lead independent AI research on large language models and agentic systems from hypothesis through production deployment. Design post-training experiments using SFT, RLHF, RLAIF, DPO, and related techniques; develop evaluation benchmarks, synthetic data pipelines, and agentic reasoning methods. Shape model architecture and training roadmaps, publish at leading AI venues, and mentor researchers and engineers. The hybrid role is based in San Francisco or New York City.
Top Skills: Adversarial Dataset ConstructionAgentic SystemsDpoGrpoJaxLarge Language ModelsLlm-As-JudgeMachine LearningNlpPythonPyTorchReinforcement Learning From Human FeedbackRlaifSupervised Fine-TuningSynthetic Data Generation
2 Days Ago
In-Office
San Francisco, CA, USA
Senior level
Senior level
Healthtech
Leads quantitative modeling, simulation, and computational research for tuberculosis drug regimen development. Develops PK/PD, mechanistic, Bayesian, QSP, and AI/ML models; integrates preclinical, clinical, and real-world datasets; supports dose optimization, trial design, and translational decisions. Provides scientific leadership across an international consortium, communicates findings, contributes to publications and grants, mentors scientists, and manages interdisciplinary research projects.
Top Skills: Artificial IntelligenceBayesian ModelingClinical Trial SimulationMachine LearningMechanistic ModelingPharmacometricsPk/Pd ModelingPythonQuantitative Systems PharmacologyRScientific Computing

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account