Senior Data Scientist
Senior Data Scientist
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
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 wed 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.
Qualifications :
What Skills you will Need
- Bachelors 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.
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 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 lifes challenges.
- Well-being Initiatives: Access to including health programs webinars and events.
- Work-Life Balance: FlexWork arrangements to support personal and professional life.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
