Staff AI Scientist

Uniphore Technologies North America Inc; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Stock options

Medical, dental, vision

401(k) with match

Generous paid time off

Job summary

Uniphore Technologies North America Inc. is hiring a senior ML professional to design and deploy AI systems capable of multi-step reasoning and decision-making for enterprise workloads.

You will lead experimentation across prompts, agents, models, and tools while ensuring latency, cost, and reliability targets. You will mentor junior scientists, collaborate with engineering teams on integration, and influence technical direction with evidence-based recommendations.

Qualifications

• MS or PhD in Computer Science, Machine Learning, Operations Research, Statistics, or related fields.
• 5+ years designing, building and iterating on ML systems with hands-on experience using frontier models and open-source models.
• Experience translating business impact into quantitative metrics and designing experiments and statistical analysis.

Responsibilities

• Design and implement AI systems capable of handling complex workflows, including multi-step reasoning, planning, and decision-making.
• Explore and apply orchestration patterns and architectures to solve business problems.
• Translate abstract requirements into reliable AI behaviors under constraints like latency and cost.
• Lead systematic experimentation across prompts, agents, model variants, and tool configurations.
• Define and implement evaluation strategies for agentic systems, including task success and robustness.
• Develop benchmarks, simulations, and offline/online evaluation loops to guide rapid iteration.
• Fine‑tune and adapt foundation models using PEFT, SFT, distillation, and RL.
• Balance performance, latency, and cost for enterprise workloads.
• Contribute to model selection decisions (SLMs vs. larger models).
• Own bounded, end-to-end AI workflows from framing through deployment.
• Partner with engineering teams on integration, monitoring, and lifecycle management.
• Act as a technical reference point for agentic AI practices.
• Mentor junior scientists on experimentation methodology and evaluation design.
• Influence roadmap and technical direction with evidence-backed recommendations.

Skills

ML systems experience

Experimentation design

Cross-functional collaboration

Communication skills

Education

MS or PhD in Computer Science / ML / OR / Statistics

Tools

Frontier models

Open-source models

Job description

Location: Palo Alto, CA

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 decision making.
• Fine‑tune and adapt small and medium‑sized foundation models using techniques such as PEFT, SFT, distillation, and reinforcement learning.
• Balance performance, latency, and cost for enterprise‑grade workloads.
• Contribute to model selection decisions (SLMs vs. larger models) based on use‑case requirements and empirical evidence.
• Own bounded, end‑to‑end AI workflows from problem framing through deployment to accelerate impact.
• Partner with engineering teams on integration, monitoring, and lifecycle management.
• Contribute to production readiness without acting as a full‑time platform or infrastructure owner.
• 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 evidence‑backed recommendations.

Minimum Qualifications

• Education: MS or PhD in Computer Science, Machine Learning, Operations Research, Statistics, or related fields.
• 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 working with cross‑functional teams to deliver ML capabilities to 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 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.

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.