About the Role
Our client, Nextgenpros Inc, is seeking an 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.
Responsibilities
- 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.