About the Role
KogniVera is seeking an experienced AI/ML Lead to design, develop, and deploy scalable machine learning models for travel & retail use cases. This is a full-time, onsite position based in Bangalore, India, requiring 10+ years of experience.
Key Responsibilities
- Design, develop, and deploy scalable machine learning models for travel & retail use cases such as:
- Personalized recommendations (hotels, destinations, packages)
- Price prediction and demand forecasting
- Route optimization (multi-city travel planning)
- Customer segmentation and behaviour analysis
- Build and maintain end to end ML pipelines (data ingestion → preprocessing → training → evaluation → deployment)
- Work with large datasets (structured and unstructured) including user behaviour, bookings, and search data
- Integrate ML models into production systems via APIs and microservices
- Collaborate with product, engineering, and business teams to translate requirements into ML solutions
- Implement experimentation frameworks (A/B testing) and continuously improve model performance
- Explore and integrate modern AI approaches such as:
- Generative AI (LLMs for travel assistants)
- RAG-based systems for conversational search
- Vector search and similarity-based retrieval
Required Skills & Qualifications
- 4–6 years of experience in AI/ML or Data Science roles (Note: Overall experience required is 10+ years)
- Experience working with Google CX Agent
- Experience working with Google Vertex AI and vector database
- Experience working with Google Commerce search
- Strong hands-on experience in Python (NumPy, Pandas, Scikit-learn)
- Experience with at least one end-to-end ML project in production
- Solid understanding of ML algorithms:
- Regression, Classification, Clustering
- Recommendation Systems (Collaborative/Content-based)
- Experience with model deployment (Flask/FastAPI, Docker, APIs)
- Good understanding of data structures, algorithms, and statistics
- Experience working with databases (SQL/NoSQL)
- Understanding of models like co-sin similarity etc.
- Understanding coding agents architecture and implementation.