Description
Grab is Southeast Asia's leading superapp, dedicated to improving the lives of millions of users across the region. We provide everyday services such as deliveries, mobility, financial services, enterprise services, and others.
We are looking for a Senior Machine Learning Engineer to join our team. As a Senior Machine Learning Engineer, you will be responsible for building advanced real-time sensing capabilities to help our driver partners work more efficiently. You will leverage your expertise in machine learning to optimize navigation experiences, including scene refinement, navigation positioning, guided optimization, user customization, interaction with real-time signals, data embedding, and analysis.
Key Responsibilities:
- Build reliable L3/L4 intelligent processes and develop robust and scalable solutions to handle real-time signals.
- Construct a large traffic model based on massive user trajectory data to enhance ETA route planning capabilities.
- Develop visual-based traffic event perception models using low-cost visual devices such as mobile phones or vehicle-mounted dashcams.
- Design, build, and maintain reliable data pipelines covering real-time stream processing and large-scale batch processing.
- Transform raw and noisy data into trustworthy features, insights, and datasets to support route planning, navigation, road conditions, and map quality-related applications.
- Establish monitoring, data quality inspection, evaluation frameworks, and feedback loops to ensure the reliability of data pipelines and model outputs.
- Collaborate closely with product managers, data scientists, analysts, and engineers to define problems, conduct experiments, and deliver scalable solutions.
- Explore emerging technologies and apply them pragmatically to improve team engineering efficiency and product results.
Requirements:
- At least two years of experience in machine learning engineering.
- Solid computer science fundamentals, including algorithms and data structures.
- Experience in developing and maintaining large-scale microservices.
- Practical experience in building and operating production-level batch and real-time data processing pipelines.
- Ability to handle noisy or incomplete data, define suitable evaluation metrics, and translate vague business issues into measurable technical solutions.
- Passion for building products and features that drive business growth.
- Familiarity with any programming language and good coding skills, with a willingness to use Golang for development.
Nice to Have:
- Experience handling geospatial, route planning, navigation, road conditions, events, or map-related data.
- Familiarity with streaming processing technologies such as Kafka, Flink, Spark Streaming, or similar systems.
- Experience building intelligent automation for engineering or operations workflows, including RAG, tool integration, assessment, and Harness engineering.
- Familiarity with data analysis, model monitoring, experimental design, and production-level ML lifecycle management.
- Familiarity with cloud services such as AWS or Azure.
Benefits:
- Term Life Insurance and comprehensive Medical Insurance.
- GrabFlex benefits package.
- Maternity and Paternity Leave.
- Confidential Grabber Assistance Programme.
- Wellbeing@Grab initiatives.
- FlexWork arrangements.