Senior Machine Learning Engineer, MLE
Core
Build advanced real-time perception and navigation algorithms for Grab's O2O platform to optimize routes, ETA, and driver efficiency using massive trajectory and visual data.
Role type
Senior Machine Learning Engineer (Navigation & Geospatial)
Builds
Real-time navigation signals, ETA prediction models, and traffic event perception systems for driver partners.
Domain
Transportation / Geospatial / O2O Superapp
Deliverable
production ML models
Required skills
Machine Learning engineering, Large-scale microservices development, Production-grade batch and real-time data pipeline construction, Noisy/incomplete data handling, Golang development, Algorithm and data structures
Preferred skills
Geospatial and route planning data experience, Stream processing technologies (Kafka, Flink, Spark Streaming), MLOps and model monitoring, Cloud platforms (AWS, Azure)
Technologies
Golang, Kafka, Flink, Spark Streaming, AWS, Azure
Responsibilities
Build reliable L3/L4 intelligent workflows for real-time signal processing; Architect traffic foundation large models based on user trajectory data; Develop visual-based traffic event perception models using low-cost devices; Design and maintain data pipelines for real-time and batch processing; Transform raw data into features and datasets for navigation and map quality; Establish monitoring and data quality frameworks; Collaborate with cross-functional teams to define problems and deliver scalable solutions.
Seniority
Senior, hands-on IC
