Machine Learning Engineer

About Grab and our workplace

Grab is Southeast Asia’s leading superapp. We are dedicated to improving the lives of millions of users across the region by providing them everyday services such as deliveries, mobility, financial services, enterprise services and others. More than that, we provide the opportunity for them to have a better life. And that aspiration starts inside Grab because we believe in a seamless blend of work and home life, making every aspect of life better for all.

Guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles—the 4Hs: Heart, Hunger, Honour and Humility—we work to create economic empowerment for the people of Southeast Asia. With our unwavering commitment to our values, we believe that we're more than a service provider; we're agents of positive change.

Get to know the team 

Grab is committed to building a leading O2O platform in Southeast Asia, where the efficiency of the platform is a crucial factor in measuring business capabilities. This team provides routing/navigation/ETA capabilities for different business verticals (transport, food delivery, express delivery, etc.). The goal is to provide the most effective and reliable real-time signals (incidents, traffic, detections from dash cams) to achieve higher platform efficiency.

Get to know the role

Here you will be deeply involved in the development of cutting-edge routings/navigation algorithms and research in the geography industry, get closer to the core metrics of the business, and use massive amounts of real data to explore their relevance to reality. Most importantly, you will have the opportunity to drive Grab's business growth through bit by bit insight and finally see the improvement of business metrics.

We are looking for a senior machine learning engineer to build advanced real-time awareness to help our driver partners finish their jobs in the most effective way. We will need your excellent MLE skills to improve our navigation experience (scene refinement, navigation positioning, guidance optimization, user customization, interaction with real-time signals, instrumentation & analytics, etc.). Also, we would like you to give full play to your talents, boldly propose creative ideas, and practice them with team members.

The Day-to-Day Activities

• Build reliable agentic L3/L4 flows to build reliable and scalable solutions to handle real-time signals.

• Design, build, and operate reliable data pipelines for both real-time streaming and large-scale batch processing, including real-time incident data and other geospatial signals.

• Transform raw and noisy data into trustworthy features, insights, and datasets that support routing, navigation, traffic, and map-quality use cases.

• Establish monitoring, data-quality checks, evaluation frameworks, and feedback loops to ensure the reliability of data pipelines and model outputs.

• Collaborate 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 the team’s engineering efficiency and product outcomes.

The Must-Haves

• 2+ years of experience in machine learning engineering.

• Strong Computer Science fundamentals in algorithms and data structures.

• Experience in 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 turn ambiguous business problems into measurable technical solutions.

• Passionate about building products and features to accelerate business growth

• You can be a good coder in any programming language, but you're willing to work in Golang. Proficiency in Golang will be a strong advantage.

The Nice-to-Haves

• Experience working with geospatial, routing, navigation, traffic, incident, or map-related data.

• Familiarity with stream-processing technologies such as Kafka, Flink, Spark Streaming, or equivalent systems.

• Experience building agentic automation for engineering or operational workflows, including RAG, tool integration, evaluation, and harness engineering.

• Familiarity with data analysis,  model monitoring, experimentation, and production ML lifecycle management.

• Familiarity with cloud systems such as AWS or Azure.

Benefits at Grab:

We care deeply about your well-being and are committed to supporting you every step of the way. Here are some of the global benefits we offer:

• Protect and provide for your loved ones with peace of mind, knowing we have your back with Term Life Insurance and comprehensive Medical Insurance.
• Craft a benefits package that suits your unique needs and aspirations with GrabFlex, because we believe in empowering you to thrive.
• Embrace the magic of new life and create lasting memories with your family through Maternity and Paternity Leave.
• Life can be overwhelming, but you're never alone. Our confidential Grabber Assistance Programme is here to guide and uplift you and your loved ones through life's challenges.
• Your well-being is our priority. Benefit from our holistic well-being initiatives through Wellbeing@Grab, including health programmes, informative webinars, and vibrant carnivals.
• Achieve a harmonious work-life balance with our FlexWork arrangements, allowing you to adapt and thrive in your personal and professional life.

We’ve got many different benefits hyper localised in each country. Speak to your recruiter during your interview to find out more.

What we stand for at Grab:

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique. If you require accommodations to fully participate in the recruitment process, you are encouraged to include your request(s) when applying.

We deliver the greatest impact and ideas when we bring together diverse perspectives. It is what enables us to spread opportunities to Grabbers and our partners. It’s not a box-ticking exercise; it’s who we are.