18 hours ago
Beijing, ChinaSenior
Responsibilities
- Build reliable L3/L4 intelligent workflows and scalable solutions for real-time signals.
- Develop traffic foundation models from large-scale user trajectory data to improve ETA and route-planning capabilities.
- Build computer-vision models using low-cost mobile or vehicle dashcam devices to detect traffic events.
- Design, build, and operate production-grade real-time streaming and large-scale batch data pipelines.
- Convert noisy and incomplete data into trusted features, insights, and datasets for routing, navigation, traffic, and map-quality applications.
- Establish monitoring, data-quality checks, evaluation frameworks, and feedback loops for pipeline and model reliability.
- Collaborate with product managers, data scientists, analysts, and engineers to define problems, run experiments, and deliver scalable solutions.
- Evaluate emerging technologies and apply them pragmatically to improve engineering efficiency and product outcomes.
Requirements
- At least two years of machine learning engineering experience.
- Strong computer science fundamentals, including algorithms and data structures.
- Experience developing and maintaining large-scale microservices.
- Hands-on experience building and operating production-grade batch and real-time data-processing pipelines.
- Ability to work with noisy or incomplete data, define appropriate evaluation metrics, and translate ambiguous business problems into measurable technical solutions.
- Strong programming and coding ability in at least one programming language, with willingness to develop in Golang.
- Experience with geospatial, route-planning, navigation, traffic, event, or map data is preferred.
- Familiarity with Kafka, Flink, Spark Streaming, or similar streaming technologies is preferred.
- Experience building intelligent automation for engineering or operations workflows, including RAG, tool integration, evaluation, and harness engineering, is preferred.
- Familiarity with data analysis, model monitoring, experimental design, and production machine learning lifecycle management is preferred.
- Familiarity with cloud services such as AWS or Azure is preferred.
Benefits
- Term Life Insurance and comprehensive Medical Insurance.
- GrabFlex benefits options.
- Maternity and Paternity Leave.
- Confidential Grabber Assistance Programme.
- Wellbeing@Grab health programs, webinars, and events.
- FlexWork arrangements.
- Benefits are localized by country and discussed with the recruiter.
Tech Stack
Categories
Data EngineeringML Engineering
About Grab
Grab builds a Southeast Asia superapp for mobility, deliveries, and financial services, serving consumers, drivers, merchants, and enterprises. It monetizes via ride and delivery commissions, merchant services (such as ads and subscriptions), and payments and digital banking products. Founded in 2012 and headquartered in Singapore, Grab operates across multiple Southeast Asian markets and is publicly listed on NASDAQ.