Lead AI/ML Engineer

Company Description

Own your logistics, own your customer experience. ShipDelight Logistics Technologies in Mumbai empowers consumer brands with an intelligent logistics platform to manage the entire product lifecycle seamlessly. Join us in transforming logistics into a strategic advantage and elevating brand customer experiences to new heights.

Role Description

Job Title: Lead AI/ML Engineer

Location: Mumbai

Company: ShipDelight Logistic Pvt. Ltd.

The Lead AI / ML Engineer will own the design, development, deployment and continuous improvement of AI-driven intelligence systems powering ShipDelight's platform. This role is responsible for transforming large-scale logistics data into accurate, explainable, scalable and production-grade AI systems that directly impact delivery promises, operational efficiency and end-customer trust.

Key Responsibilities:

• AI & ML architecture ownership
• Predictive modeling & decision intelligence
• Real-time intelligence for operations
• Data & feature engineering strategy
• MLOps deployment & model governance
• Humanised tracking & customer-facing intelligence
• Scalability, performance & reliability engineering
• Cross-functional technical leadership
• AI roadmap execution & outcome accountability

Key Accountabilities:

• End-to-end ownership of AI outcomes including the model accuracy
• Accountable for production readiness of all ML systems under ownership
• Responsible for explainability and trust - especially in customer-facing predictions
• Accountable for scalability, reliability, and long-term maintainability
• Owner of AI roadmap execution across ShipDelight platform

Technology and Tools:

• Python (mandatory)
• Scikit-learn, XGBoost, LightGBM
• PyTorch
• Statsmodels (for statistical and probabilistic modeling)
• SQL (PostgreSQL / MySQL)
• NoSQL (MongoDB or equivalent)
• Data warehousing concepts (Redshift / BigQuery / Snowflake)

Qualifications:

• 46+ years of experience in Machine Learning / Data Science / AI Engineering
• Proven experience deploying ML models into production at scale
• Strong understanding of time-series, probabilistic modeling and classification
• Ability to translate business problems into ML formulations
• Product-oriented mindset with strong ownership and accountability
• Understanding of logistics industry is a definite added plus