Machine Learning Engineer

Grab

  • Beijing
  • Permanent
  • Full-time
  • 1 day ago
Company DescriptionAbout Grab and Our WorkplaceGrab 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 DescriptionData Science, GEO - Traffic team at Grab focuses on building world-class map services such as travel time estimation, traffic activity recognition, high-precision indoor / outdoor positioning. These applications enhance Grab's consumer experience on transport, food, deliveries, logistics and optimize our platform efficiency. We extensively use state of the art deep learning techniques, computer vision and conventional machine learning models for developing services for geo-spatial intelligence. These technologies are applied on a variety of signals including GPS probes, sensor readings, images, etc. to build strong map service capabilities. We also support the development of innovative, highly scalable, models through deep research and advanced analysis so that we make our products intelligent and delight our customers. We foster a culture where we enjoy raising the bar constantly for ourselves and others, and that strongly supports the freedom to ideate, innovate, invent and create impact on day-to-day lives of millions of people.Duties and Responsibilities
  • Understands the team's end-to-end system design and can design new features/components based on clearly defined requirements.
  • Design solutions that are robust, able to handle business-as-usual (BAU) scenarios effectively, with some guidance on edge cases.
  • Develop data pipelines, build, and optimize 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 business operation teams.
QualificationsRequirements
  • Master's in Computer Science, Electrical/Computer Engineering, Operations Research, or related technical disciplines.
  • You have experience in end to end ML lifecycle from data preprocessing, model development, model deployment through model retraining and fine tuning.
  • You have experience manipulating large scale datasets using libraries such as Spark.
  • Good understanding of the 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
  • 2+ 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 InformationLife at GrabWe 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 GrabWe 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.

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