Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

Get to Know the Team

Data Science, GEO - Traffic team at Grab focuses on building world-class map services such as travel time estimation, traffic activity recognition and indoor / outdoor positioning. These applications enhance Grab's consumer experience on transport, food, deliveries, logistics and improve our platform efficiency. We use deep learning and conventional machine learning models for developing services for geo-spatial intelligence. These technologies are applied on a variety of signals such as GPS probes, sensor readings and street view images to build map service capabilities.

Get to Know the Role

As a senior data scientist you will develop pipelines and models for high QPS use cases such as travel time estimation for food, transport and positioning. You will report to the Senior Data science manager of DS-Geo-Services.

The Critical Tasks You Will Perform

• Understand our needs, identify areas for investigation and translate them to technical problems to be solved
• Define hypotheses, build necessary tests, experiments, and data analyses to prove or disprove them
• Develop data pipelines, build, and increase deep learning and machine learning algorithms—including Large Language Models (LLMs), and multi-modal models—for real-world impact.
• Contribute to team's innovation and IP creation
• Collaborate with other data scientists, software engineers, product managers and our operation teams.

Qualifications

What Essential Skills You Will Need

• Master's in Computer Science, Electrical/Computer Engineering.
• 2+ years of experience in end-to-end ML lifecycle from data preprocessing, model development, model deployment through model retraining and fine tuning.
• 2+ years of experience manipulating large-scale datasets using libraries such as Spark.
• Proficiency in deep learning frameworks such as TensorFlow or PyTorch and deployment tools (ONNX, tf-serving, TorchServe, Triton Inference Server)
• Solid software engineering skills in Python
• Experience with model versioning, CI/CD for ML, containerization (e.g., Docker), and cloud-based deployment (AWS, GCP, Azure)

Nice-to-Haves

• 3+ years of industry experience working with logistics, mapping or e-commerce data and use cases.
• Experience in ETA, traffic prediction, routing algorithm, positioning algorithm or mobile-side computing is a very desirable plus.
• Knowledge of programming in Golang or Rust.
• Know the modern data pipeline and warehousing stacks such as Airflow, Superset, Kafka stream processing and Apache Flink.
• Experience working with and finetuning Large Language models (LLMs) and agentic AI frameworks such as Langchain/Langgraph/crewAI.

Additional Information

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

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.