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As a Research Scientist/Engineer on the AI team at Sentient, you'll lead the development and implementation of techniques aimed at training language models and agents that have advanced reasoning capabilities: In particular, such AI will be able to make strategic decisions in multi-agent environments with high stakes (e.g., involving financial transactions), You'll work to develop novel post training and agentic techniques and to use these to demonstrably improve AI behavior.
Job Responsibility:
Develop and implement novel fine-tuning and reinforcement learning techniques using synthetic data generated from multi-turn interactions
Use these to design agentic systems to improve reasoning skills to be evaluated on long-horizon strategic decision making benchmarks
Create and maintain evaluation frameworks to measure reasoning skills and design new benchmarks
Requirements:
MS/PhD in Computer Science, ML, or related field, or equivalent experience
Strong programming skills, especially in Python
Experience with ML model training and experimentation
Track record of implementing ML research
Strong analytical skills for interpreting experimental results
Experience with ML metrics and evaluation frameworks
Excel at turning research ideas into working code
Can identify and resolve practical implementation challenges
Nice to have:
Experience with language model fine-tuning and post-training
Background in AI agents and/or reasoning research
Published work in AI
Experience with synthetic data generation
Familiarity with techniques like RLHF and reward modeling
Track record of designing and implementing novel training approaches
Experience with model behavior evaluation and improvement