Senior Data Scientist

Life at Grab

At Grab, every Grabber is 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. These principles guide and help us make decisions as we create economic empowerment for the people of Southeast Asia.

Get to know the Team

The Data Science (Geo Vision) team at Grab focuses on improving the maps and building map-based intelligence such as localization, routing, travel time estimation, and traffic forecasting, that assist multiple Grab services like transportation, logistics, and pricing. We use Computer Vision, NLP, Information Retrieval, and Text Mining along with conventional machine learning methods on a variety of signals including images, videos, text, sensor readings, GPS probes to understand our locations and road networks. We also support the development of innovative, scalable, models through deep research and advanced analysis so that we make our products thoughtful and delight our customers.

Get to know the Role

We are looking for a Senior Data Scientist to help automate the process of map creation using data science techniques. We believe a successful candidate has very good computer vision skills and learning expertise, but if you believe you have what it takes then we'd love to hear from you either way. This role is required because of the very impacting the maps. You will be on site and you will report to the Head of Data Science based in the Cluj Office.

The Critical Tasks You Will Perform

• You will develop object detection, positioning, instance segmentation, and tracking models in a in house learning framework
• You will train model on a large scale distributed system
• You will deploy computer vision algorithms and machine learning models into embedded platforms.
• You will collaborate with cross-functional teams to define product requirements and specifications.
• You will conduct performance analysis and fine-tuned models for optimal execution on embedded systems.
• You will stay up-to-date with the latest advancements in machine learning and computer vision technologies.

What Skills you will Need

• Bachelor's degree in Computer Science, Electrical Engineering, or related field.
• Minimum of 4 years of experience in computer vision and machine learning.
• Experience with image processing algorithms, including advanced computer vision techniques such as projective geometry, camera localization, motion estimation, and 3D reconstruction.
• Knowledge and practical experience in designing, training, evaluating, and optimizing Deep Learning networks.
• Experience with Python and some of the following libraries: OpenCV, PyTorch, and TensorFlow.
• Experience with distributed training frameworks like DDP, Ray, Horovod
• Understanding of machine learning methods for classification, regression, and clustering.
• Knowledge of projective geometry, linear algebra, and numerical optimization.
• Possess proficiency in English, both in speaking and writing and can present data insights and results through compelling visualizations.

The Nice-to-Haves

• Experience with Hugginface Transformers library
• Experienced with camera localization and motion estimation using a combination of the following sensors: GPS, IMU, video, and magnetometer.
• Proficient in system-level software, in particular hardware-software interactions and resource utilization.
• Knowledge of optimization techniques for resource-constrained environments.

Our Commitment

We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity sexual orientation, and other attributes that make each Grabber unique.

Benefits at Grab:

• Insurance: Comprehensive Term Life Insurance and Medical Insurance.
• Customized Benefits: GrabFlex offers a tailored benefits package.
• Parental Leave: Maternity and Paternity Leave for new parents.
• Support Programs: Confidential Grabber Assistance Programme for life's challenges.
• Well-being Initiatives: Access to , including health programs, webinars, and events.
• Work-Life Balance: FlexWork arrangements to support personal and professional life.