Research Scientist, Llm Evaluation & Post-training

Centific Global

Palo Alto, CA, US
Base: $150k - $300k annually; bonus/equity: not sp...
Hybrid
Llm evaluation framework development
Post-training techniques sft rlhf dpo
Statistical analysis and experimental design
Centific Global is seeking a Research Scientist specializing in LLM Evaluation & Post-Training to drive model improvement through evaluation design and measurement strategies. This role combines applied ML research, enterprise AI product development, and customer engagement to enhance Centific's AI capabilities

Job Summary

  • This role sits at the intersection of applied ML research, enterprise AI product development, and customer-facing scientific consulting to drive model improvement.
  • The successful candidate will lead research programs defining next-generation evaluation-driven post-training workflows and develop rigorous benchmark frameworks.
  • Centific empowers leading AI organizations with safe, scalable AI deployment by bridging the gap between AI creators and industry leaders.

Matching Summary

Match Score: 85

Centific Global is seeking a Research Scientist specializing in LLM Evaluation & Post-Training to drive model improvement through evaluation design and measurement strategies. This role combines applied ML research, enterprise AI product development, and customer engagement to enhance Centific's AI capabilities.

Salary

Base: $150K - $300K Annually; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • LLM evaluation framework development
  • Post-training techniques SFT RLHF DPO
  • Statistical analysis and experimental design
  • Python coding for ML research pipelines
  • Human evaluation protocols and QA

Nice-to-have

  • Multimodal and long-context benchmarking
  • Agentic evaluation protocol design
  • Top-tier conference publication record
  • Customer-facing technical consulting experience
  • Safety and governance in GenAI

Key Requirements

  • MS or PhD in Computer Science or related quantitative field
  • 5+ years of relevant experience in applied ML research
  • Demonstrated expertise in LLM evaluation and alignment
  • Strong proficiency in PyTorch, Hugging Face, or JAX

Work Rights

Not specified

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