Senior Computer Vision EngineerRomania
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 work to 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 various Grab services like transportation, logistics, and pricing. We extensively 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, etc to understand our locations and road networks. 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 explore and innovate.
Get to know the Role
We are looking for a Senior Computer Vision Engineer to help automate the process of map creation using data science techniques. We believe a successful candidate has very good modern computer vision skills and strong deep 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 fast pace of change in the SE-Asia environment impacting deeply the maps. In return, you will get an opportunity to grow in a very challenging environment requiring innovation and creativity.
The Day-to-Day Activities
Solve object detection, positioning, instance segmentation, and tracking.
Deploy computer vision algorithms and machine learning models into embedded platforms.
Collaborate with cross-functional teams to define product requirements and specifications.
Conduct performance analysis and fine-tune models for optimal execution on embedded systems.
Stay up-to-date with the latest advancements in machine learning and computer vision technologies.
Bachelor’s degree in Computer Science, Electrical Engineering, or related field.
Minimum of 3 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.
Robust knowledge and practical experience in designing, training, evaluating, and optimizing Deep Learning networks.
Experience with Python and some of the following libraries: OpenCV, PyTorch, TensorFlow.
Understanding of machine learning methods for classification, regression, and clustering.
Knowledge of projective geometry, linear algebra, numerical optimization.
A highly driven individual who consistently stays informed about the latest developments and advancements in computer vision and deep learning methodologies and architectures.
Possesses strong English communication skills, both in speaking and writing and has the ability to effectively present data insights and results through compelling visualizations.
Experienced with camera localization and motion estimation using a combination of the following sensors: GPS, IMU, video, magnetometer.
Proficient in system-level software, in particular hardware-software interactions and resource utilization.
Knowledge of optimization techniques for resource-constrained environments.
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.
Grab is an equal opportunity employer. We owe our success to the talents of our globally-diverse team and the varying perspectives they add to our thriving community.
Grab does not accept unsolicited resumes sent by recruiting agencies. Please do not forward resumes to our job postings, Grab employees or other parts of the business. Grab will not be liable to pay any fees to agencies for candidates hired as a result of unrequested resumes.