AI Research Scientist (LLMs)

Key Responsibilities:

• Research Leadership & Technical Direction
• Lead research and development for conversational AI, agentic AI, and multi-step reasoning systems
• Explore and prototype novel architectures, algorithms, and interaction paradigms across text, voice, and multi-modal interfaces
• Define technical roadmaps, research priorities, and model evaluation strategies for agent behaviors, tool-use workflows, and context management


Modeling & System Development
• Develop agent frameworks including prompt architectures, retrieval systems (RAG), planning modules, and tool orchestration pipelines
• Build robust real-time systems including voice streaming, low-latency inference, and continuous context tracking
• Design, fine-tune, and deploy LLM-based and multi-modal models using internal infrastructure, REST APIs, and microservices
• Run systematic experiments to evaluate model quality, reliability, reasoning, and user experience
• Analyze conversational data, agent behavior traces, and performance metrics to guide iterative improvements
• Develop benchmarking protocols, simulation environments, and evaluation tooling for agentic workflows


Data & Infrastructure Ownership
• Build and curate high-quality datasets for training and evaluation, including preprocessing, labeling workflows, and data governance
• Ensure data accuracy, reproducibility, and rigor across the research lifecycle
• Collaborate with backend and ML infrastructure teams on scalable deployment, monitoring, and optimization of agentic systems


Cross-functional Collaboration
• Partner with product teams to translate research into production features
• Work with engineering teams to ensure reliability, safety, and performance of deployed models
• Contribute to internal documentation, research reports, and knowledge-sharing sessions

Key Requirements:

• PhD in Artificial Intelligence, Computer Science, Machine Learning, or a related technical field
• Prior research experience with Machine Learning / AI required
• Strong proficiency in Python, with experience in ML frameworks (e.g., PyTorch) and data tooling (NumPy, Pandas, Scikit-learn)
• Demonstrated experience in NLP, LLMs, conversational AI, or machine learning research
• Strong problem-solving skills and ability to operate independently while driving complex research initiatives
• Experience designing experiments, evaluating models, and working with large datasets

Preferred Qualifications:

• 2+ years of research or applied ML experience in conversational agents, LLM systems, or real-time AI applications
• Experience deploying models or research prototypes to cloud environments 
• Expertise with RAG pipelines, vector databases, reasoning or planning modules, or agent tool-use systems