Research Scientist, Post-Training at fast-growing conversational AI startup

You will drive model alignment and performance for next-generation speech-to-speech AI. This role involves hands-on research, data curation, and executing training experiments using RLHF and SFT to improve emotional intelligence in dialogue. You will work with large-scale models and massive datasets to bridge the gap between transactional exchanges and natural, human-like conversations.

Fast-growing conversational AI startup

• Lead post-training workflows including supervised fine-tuning (SFT) and preference optimization (RLHF/DPO) for large-scale models.
• Curate high-quality datasets and design automated or human-in-the-loop evaluation frameworks to measure model performance.
• Formulate and test hypotheses to improve model alignment, emotional context, and real-time dialogue management.

• PhD in Machine Learning or related field with publications at top-tier conferences like NeurIPS or ICML.
• Hands-on experience training 1B+ parameter models, specifically in LLM post-training or state-of-the-art speech modeling.
• Proven ability to thrive in early-stage environments with a focus on shipping fast and obsessing over user experience.

• Work on cutting-edge duplex AI architectures that move beyond traditional walkie-talkie style voice interactions.
• Join a mission-driven founding team backed by top-tier VCs and prominent technology industry leaders.
• Significant equity and high autonomy in an environment designed for rapid iteration and shipping research to production.