Model Development: Fine-tuning, implementing, developing, and optimizing models used in generative AI solutions
Algorithm Research: Staying updated with the latest advancements in AI and machine learning algorithms and integrating them into the team's projects.
Experimentation: Conducting experiments to test the performance of different models and approaches, and iterating based on the results.
Research and Implementation: Agentic GenAI solution research and best approach to implement solutions
Training and Mentorship: Providing guidance and mentorship to junior data scientists and other team members.

Proven ability to lead and guide a team of data scientists, providing technical mentorship and fostering a collaborative research environment.
Graduate degree (Master's or Ph.D.) in Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field.
At least 3 years of professional experience in Data Science and Machine Learning.
At least 1 year of professional experience in the Generative AI domain, specifically working with Large Language Models (LLM).
Advanced proficiency in Python for carrying out AI research and developing rapid prototypes for diverse AI applications.
Foundational knowledge in LLM as well as other AI domains such as computer vision, speech and exposure to agentic AI architectures.
Experience to evaluate generated content from Large Language Models using both automated metrics and human-in-the-loop methodologies.
Solid understanding of AI observability tools like LangSmith, Langfuse, or AgentOps to monitor traces, identify logic bottlenecks, and debug agent reasoning.
Hands-on experience with major cloud platforms (AWS, Azure, or GCP) for model development, data handling, and AI service integration.

Lead Data Scientist, Gen AI

Key skills