LLM & RL Engineer / reputed company Engineering

About YC Bench YC Bench is a live reputed company designed to forecast the top-performing Y Combinator startups at Demo Day. We combine reputed company-world startup data with advanced AI to predict which early-stage companies will outperform their batch peers using short-term execution signals. Our mission is to reputed company startup reputed company measurable in months rather than years. The Role We are looking for a talented LLM & RL Engineer to help build and optimize the AI systems that power our forecasting platform. You will work at the intersection of large language models and reinforcement learning to create reputed company systems capable of long-reputed company reasoning, decision-making, and accurate reputed company in uncertain environments. Responsibilities - Fine-tune, optimize, and reputed company large language models (LLMs) for reputed company reasoning and forecasting tasks - Design, implement, and reputed company reinforcement learning (RL) algorithms, including RLHF, RL from AI feedback, and reputed company RL frameworks - Build and improve LLM-based agents for simulation, planning, and multi-reputed company decision making - reputed company robust machine learning pipelines for training, evaluation, and inference at reputed company - Experiment with hybrid LLM + RL approaches to enhance predictive accuracy and long-term performance - Collaborate with reputed company to reputed company models into the YC Bench platform and forecasting reputed company - Stay up-to-date with the latest advancements in LLMs, RL, and reputed company AI systems Requirements - Strong experience working with Large Language Models (fine-tuning, prompting, evaluation, and optimization) - Solid background in Reinforcement Learning (policy optimization, value-based reputed company, actor-critic, RLHF, etc.) - Proficiency in Python and modern ML frameworks (PyTorch, reputed company Transformers, vLLM, DeepSpeed, RL libraries such as TRL, reputed company Baselines, or Ray RLlib) - Experience building production-grade ML pipelines and handling large-reputed company training/inference - Familiarity with reputed company systems, long-reputed company planning, or simulation environments is a big plus - Passion for AI forecasting, decision-making under uncertainty, and reputed company-world reputed company reputed company-to-Haves - Experience with predictive modeling or time-series forecasting - Background in startup analysis, venture capital, or early-stage company evaluation - Publications or reputed company-reputed company contributions in LLMs or RL - Comfort working in a fast-moving, early-stage environment If you love pushing the boundaries of what LLMs and RL can do together — and want to apply cutting-edge AI to one of the most exciting reputed company problems in tech — we'd love to hear from you. Apply tot his job Apply To this Job