Machine Learning Engineer (Fulfilment ETA)
Core
Building Deep Neural Network models to predict Estimated Time of Arrival (ETA) for food orders and transport bookings, while optimizing ETA quotations to balance accuracy, system efficiency, and marketplace throughput.
Role type
Machine Learning Engineer (ETA Prediction & Optimization)
Builds
Production ML models for ETA prediction and optimization, automated retraining pipelines, and monitoring dashboards.
Domain
Logistics, Food Delivery, Transportation
Deliverable
production ML models
Required skills
Deep Learning, Machine Learning, Causal Inference, Operation Research, Python, TensorFlow/PyTorch, SQL, Spark, ETL pipeline development, Version Control (git)
Preferred skills
Experience in tech companies or machine learning industry
Technologies
TensorFlow, PyTorch, Spark, SQL, git
Responsibilities
Develop DNN models to predict ETA accurately under uncertainty; build optimization models to balance ETA accuracy and system efficiency; establish automated pipelines for model retraining and parameter tuning; build dashboards to monitor model accuracy and service health; create technical documentation; present solutions to non-technical stakeholders; collaborate on A/B experiments and data analysis.
Seniority
Mid-level (2+ years experience)