Senior AI/NLP Research Engineer - Production ML

WisdomAI; San Mateo (CA); On-site; USD 238,000 - 322,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

WisdomAI in California seeks a senior ML/NLP researcher to design and run rigorous experiments, improve NL-to-SQL generation, and advance multi-turn conversational understanding. You will prototype, validate, and productionize ML techniques, including fine‑tuning, distillation, and retrieval optimization, while evaluating new foundation models for rapid production impact.

The role emphasizes data‑driven decisions balancing quality, latency, cost, and reliability, with a strong focus on producing

Qualifications

• Master's degree in CS/ML/AI/NLP required; PhD a strong plus.
• Proven track record shipping production AI systems.
• Deep experience with modern LLMs and agent architectures.
• Strong software engineering with production‑quality Python.

Responsibilities

• Design and run rigorous experiments to improve NL-to-SQL generation, retrieval, ranking, and agentic reasoning.
• Advance multi-turn conversational understanding with memory, context retention, and clarification strategies.
• Build robust evaluation frameworks, benchmarks, and LLM-as-a-judge methodologies.
• Prototype, validate, and productionize ML techniques including fine‑tuning, distillation, and retrieval optimization.
• Evaluate emerging foundation models and translate advances into production experiments.
• Contribute to the AI community via technical reports or conference talks.

Skills

Applied ML

NLP

LLMs

Python

Production AI

Experimentation

Education

Master's degree in CS/ML/AI/NLP

PhD preferred

Tools

Python (production)

AI frameworks (PyTorch/TensorFlow)

Job description

WisdomAI in California seeks a senior ML/NLP researcher to design and run rigorous experiments, improve NL-to-SQL generation, and advance multi-turn conversational understanding. You will prototype, validate, and productionize ML techniques, including fine‑tuning, distillation, and retrieval optimization, while evaluating new foundation models for rapid production impact.

The role emphasizes data‑driven decisions balancing quality, latency, cost, and reliability, with a strong focus on producing