🛠 Tech Stack

💼 About This Role

You'll design and deploy predictive ML models for supply chain transportation analytics, directly improving delivery efficiency and decision-making. You'll own the end-to-end lifecycle from feature engineering to production deployment using Google Vertex AI.

🎯 What You'll Do

• Design and optimize XGBoost models for transportation use cases.
• Perform feature engineering, selection, and experiment design.
• Conduct exploratory data analysis on logistics datasets.
• Deploy ML models to production using Google Vertex AI.

📋 Requirements

• 7+ years in Machine Learning or Data Science.
• Hands-on experience building models with XGBoost.
• Experience in Supply Chain or Transportation Analytics.
• Proficiency in Python and SQL for ML development.

✨ Nice to Have

• Experience deploying ML on Google Vertex AI.
• Familiarity with MLOps and end-to-end ML lifecycle.

🎁 Benefits & Perks

• 📈 Competitive Salary
• 🏥 Statutory Major Benefits
• 📚 Personal Growth opportunities
• 🎁 Attractive benefits plan

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min