AI Research Scientist LLM & RL

AI Researcher with deep expertise in LLM fine-tuning, reinforcement learning, recommendation systems, and anomaly detection. You will be part of a cutting-edge team driving innovation in applied AI, delivering models and solutions that power real-world applications.

• Design and implement fine-tuning pipelines for large language models (LLMs) using open-source and proprietary datasets.
• Conduct research and develop models based on reinforcement learning (RL) frameworks such as PPO, DDPG, or A3C.
• Build and optimize recommendation engines leveraging collaborative filtering, matrix factorization, and deep learning.
• Develop and deploy anomaly detection models using statistical, unsupervised, and neural network approaches.

Qualifications:

• Advanced degree (PhD or Master's) in Computer Science, Machine Learning, Data Science, or related field
• Strong background in LLM fine-tuning (e.g., LoRA, PEFT, RLHF, prompt tuning)
• Hands-on experience with reinforcement learning algorithms and toolkits (e.g., Ray RLlib, OpenAI Gym, Stable Baselines3)
• Solid understanding of recommendation system architectures (collaborative filtering, deep learning, hybrid models)
• Experience in anomaly detection using techniques such as Isolation Forest, Autoencoders, or One-Class SVM
• Proficiency in Python and libraries like PyTorch, TensorFlow, Hugging Face Transformers, Scikit-learn, and Pandas