AI Engineer

Develop, fine-tune, and deploy Large Language Models (LLMs) for real-world applications.
Design and implement advanced Reinforcement Learning (RL) algorithms to improve AI performance.
Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate AI solutions into business systems.
Optimize model architecture and performance for scalability and efficiency.
Conduct research and stay updated on the latest AI advancements to enhance the company’s AI capabilities.
Evaluate and continuously improve AI models using feedback loops and performance metrics.

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Proven experience in building and fine-tuning Large Language Models (e.g., GPT, LLaMA, Qwen).
Strong expertise in Reinforcement Learning (RL) with knowledge of frameworks such as RLlib and Stable Baselines.
Proficiency in Python and experience with machine learning frameworks like TensorFlow or PyTorch.
Solid understanding of natural language processing (NLP), neural networks, and transformer-based architectures.
Experience with distributed computing and deploying large-scale AI models.
Familiarity with cloud platforms (AWS, GCP, or Azure) for AI/ML deployment.
English communication skills (both written and spoken) to collaborate with international teams and clients effectively.
Strong analytical and problem-solving skills, with the ability to work both independently and collaboratively.
Preferred Qualifications:
Experience in human feedback-based model training (Reinforcement Learning with Human Feedback - RLHF).
Knowledge of MLOps practices for seamless deployment and monitoring of AI models.
Research experience or publications in LLMs or Reinforcement Learning.