AI Scientist Intern developing and implementing models for healthcare solutions. Collaborating with AI teams to drive data - driven decision making.
About the role
- AI Research Scientist at Lendbuzz developing conversational AI and agentic AI systems. Leading research direction and collaborating with cross-functional teams in a hybrid work environment.
Responsibilities
- 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
- 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
- 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
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
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