AI Researcher

Accountabilities:

• Conduct advanced research on agentic AI systems trained on real-world interaction data.
• Design and experiment with learning frameworks such as RAG, fine-tuning, RLHF, DPO, and GRPO.
• Develop multimodal representation learning approaches across text, audio, logs, and structured data.

Requirements:

• PhD in Computer Science, Machine Learning, AI, or related field with 5+ years applied research experience.
• Strong expertise in large-scale ML, LLMs, multimodal AI, and reinforcement learning methods.
• Proficiency in Python, PyTorch, Hugging Face, and evaluation frameworks for LLMs.

Benefits:

• Fully remote position within a global AI research organization.
• Opportunity to shape cutting-edge agentic and multimodal AI systems.
• Access to large-scale proprietary datasets and AI infrastructure.