Machine Learning Engineer

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, build, and deploy supervised and unsupervised machine learning models to create user personas using large-scale behavioral and user interaction data.
• Develop, optimize, and maintain recommendation systems to personalize destinations, itineraries, and content for users.
• Train, test, evaluate, and monitor machine learning models to ensure performance, scalability, and accuracy in production environments.
• Build and maintain efficient ETL data pipelines to support information retrieval and multiple downstream use cases.
• Document model experiments, evaluations, and performance metrics using Weights & Biases (W&B).
• Work comfortably with AWS services, including EC2, S3, and Load Balancers, to deploy and scale ML systems.
• Stay current with advancements in
  
  machine learning, recommender systems, and applied AI, and apply relevant innovations to production systems.
• Design and implement agentic workflows using LangGraph, and build information retrieval systems leveraging vector databases for RAG use cases.
• Work with large embedding models for information retrieval, with 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 closely with product managers, data analysts, and backend engineers to translate business objectives into effective ML solutions.

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Requirements

• 35 years of hands-on experience in core machine learning or applied AI roles
• Proven experience building recommendation systems, personalization engines, or user-facing ML features
• Strong understanding of machine learning fundamentals, including supervised and unsupervised learning, feature engineering & building training datasets for models to be trained on.
• Solid foundation in probability, statistics, and algorithms
• Proficiency in Python and experience with ML frameworks such as PyTorch & 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 well-defined ML objectives
• Strong analytical, problem-solving, and communication skills
• Bachelors degree in Computer Science, Mathematics, Engineering, or a related field (or equivalent practical experience)
• Worked in a fast paced AI-based startup environment with high flexibility.