Lead Data Scientist

Get to know the Team

The Data Science (Geo Vision) team at Grab focuses on improving maps and building map-based, such as localization, routing, travel time estimation, and traffic forecasting. These efforts support various Grab services including transportation, logistics, and pricing. We utilize Computer Vision, NLP, Information Retrieval, Text Mining, and conventional machine learning techniques to process a variety of signals such as images, videos, text, sensor readings, and GPS probes to understand locations and road networks. Our deep research and advanced analysis contribute to the development of innovative, highly scalable models that make our products thoughtful and delightful for our customers. Our culture emphasizes continuous improvement, exploration, and innovation.

Get to know the Role

We are looking for a Lead Data Scientist to help automate map creation using data science techniques. A successful candidate will excel in modern computer vision and deep learning. This role is crucial due to the rapid changes in the SE-Asia environment that impact maps. You will have the opportunity to grow in a workplace that demands innovation and creativity. The role is hybrid and you will report to the Senior Engineering Manager based in the Cluj Office.

The Critical Tasks You Will Perform

• You will involving object detection, positioning, instance segmentation, and tracking.
• You will deploy computer vision algorithms and machine learning models on embedded platforms.
• You will collaborate with cross-functional teams to define product requirements and specifications.
• You will conduct performance analysis and fine-tune models for optimal execution on embedded systems.
• You will stay current with the latest advancements in machine learning and computer vision technologies.

Requirements

What Skills You Will Need

• Educational Background: Bachelor's degree in Computer Science, Electrical Engineering, or a related field.
• Computer Vision Expertise: At least 3 years of experience in image processing algorithms, projective geometry, camera localization, motion estimation, and 3D reconstruction.
• Deep Learning Proficiency: Experience in designing, training, evaluating, and optimizing Deep Learning networks.
• Programming Skills: Proficiency in Python and familiarity with libraries such as OpenCV, PyTorch, and TensorFlow.
• Machine Learning Knowledge: Understanding of classification, regression, and clustering methods.
• Mathematical Expertise: Knowledge of projective geometry, linear algebra, and numerical optimization.
• Continuous Learning: A strong drive to stay updated with the latest developments in computer vision and deep learning methodologies.
• Communication Skills: Proficient in English

Nice-to-Haves

• Sensor Integration: Experience with camera localization and motion estimation using sensors like GPS, IMU, video, and magnetometer.
• System-Level Software: Proficiency in hardware-software interactions and resource utilization.
• Optimization Techniques: Knowledge of optimization techniques for resource-constrained environments.

Additional information

Our Commitment

We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best. We consider all candidates fairly, regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, or any 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 Wellbeing@Grab, including health programs, webinars, and events.
• Work-Life Balance: FlexWork arrangements to support personal and professional life.