Overview
EightyDays is a travel technology company focused on reimagining how users discover, plan, and experience travel. We are a Mumbai-based travel tech startup that simplifies trip planning by helping users discover and organize hidden gems and unique experiences. The platform leverages AI to transform how people plan and share adventures.
Responsibilities
- Design, develop, and deploy supervised and unsupervised machine learning models to generate user personas from large-scale behavioral and user interaction data.
- Develop, enhance, and maintain recommendation systems to personalize destinations, itineraries, and content for users.
- Train, validate, evaluate, and monitor machine learning models to ensure strong performance, scalability, and accuracy in production environments.
- Build and manage efficient ETL data pipelines to support information retrieval and multiple downstream applications.
- Document model experiments, evaluations, and performance metrics using Weights & Biases (W&B).
- Work with AWS services such as EC2, S3, and Load Balancers to deploy and scale machine learning systems.
- Stay up to date with advancements in machine learning, recommender systems, and applied AI, and incorporate relevant innovations into production systems.
- Design and implement agentic workflows using LangGraph, and develop information retrieval systems leveraging vector databases for RAG use cases.
- Work with large embedding models for information retrieval, including an understanding of fine-tuning techniques.
- Build and maintain similarity-based retrieval systems using vector databases and NoSQL technologies such as MongoDB and Elasticsearch.
- Integrate Model Context Protocol (MCP) with agentic systems to enable scalable and modular AI workflows.
- Collaborate with project manager, data analyst, and backend engineers to translate business requirements into effective machine learning solutions.
Requirements
- Minimum 35 years of hands-on experience in core machine learning or applied AI roles
- Demonstrated experience building recommendation systems, personalization engines, or other user-facing ML features
- Strong understanding of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, and building training datasets for model development
- Solid foundation in probability, statistics, and algorithms
- Proficiency in Python with experience using ML frameworks such as PyTorch and TorchServe
- Experience working with large datasets and production-grade ML pipelines
- Familiarity with data modeling, data structures, and software engineering best practices
- Ability to translate ambiguous business problems into clearly defined ML objectives
- Bachelor's degree in Computer Science, Mathematics, Engineering, or a related field (or equivalent practical experience)
- Preferred working in a fast-paced AI-driven startup environment with a high degree of flexibility
