Are you passionate about using your Computer Vision and Deep Learning expertise to make a positive impact in the world? If yes, this is the opportunity for you. We are seeking a highly skilled Computer Vision and Deep Learning Engineer with experience in Point clouds, computer vision, and API knowledge such as Google ARcore to join our team at Child Growth Monitor (CGM). Our mission is to prevent malnutrition in children by turning mobile phones into child-measuring devices. Through the use of augmented reality and artificial intelligence, we can accurately predict a child's height, weight, and middle upper-arm circumference to determine their nutritional status.
As a Computer Vision and Deep Learning Engineer, you will be responsible for:
· Responsible for developing and implementing computer vision and deep learning solutions for our company's products.
· Develop and implement computer vision and deep learning algorithms for depth maps, point clouds, and computer vision applications
· Work with point cloud/depth map data, including data acquisition, pre-processing, and analysis
· Implement and optimize computer vision and deep learning models for real-time applications
· Nice to have: Work with Google AR core API and other relevant technologies to integrate computer vision and deep learning solutions into products.
· Collaborate with cross-functional teams to identify and solve problems related to computer vision and deep learning.
· Stay up-to-date with the latest advancements in computer vision and deep learning
To be successful in this role, you should have:
- Strong experience in point clouds, 3D computer vision, and deep learning (with 2-5 years of industry experience)
- Experience with Google AR core API or other relevant technologies
- Proficient in programming languages such as Python/C++
- Experience with computer vision libraries such as OpenCV and deep learning frameworks such as TensorFlow
- Strong problem-solving skills and ability to work in a team environment
- Strong written and verbal communication skills
- Experience in real-time computer vision and deep learning applications is a plus
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field
Why should you join us?
This is a full-time consultant position and remotely based and within 2 hrs overlap of GMT +5:30 time zone.
As part of the Welthungerhilfe team, you will have the opportunity to work with a global organization committed to ending hunger and malnutrition by 2030. Most importantly, you will have the satisfaction of knowing that your work is helping to save the lives of millions of children.
More than this generous/competitive remuneration, you’ll be doing the work of a lifetime with Child Growth Monitor. It’s a moonshot project just like autonomous car driving that no one has figured out completely yet. Your contribution can save the lives of 3 million children under age 5 who die from untimely diagnosis of malnutrition. Apart from this, you’ll have the opportunity to collaborate and publish papers with WHO, UNICEF, Microsoft, Tilburg University, respected independent researchers, etc.. You enjoy Flat culture, a friendly environment, teams making decisions, and a work-life balance. There are endless opportunities that you can work on.
Our Hiring Process
You apply
1. We short-list
2. [20 min] Preliminary discussion with HR
3. [2 working days] Assignment – Optional for Senior levels
4. [60 min] In-depth interview: 1st Domain/Technical round screen with the product team member
5. [60 min] In-depth interview: 2nd Domain/Technical Round with the product team member
6. [60 min] Interview with Product Head & HR (Behavioral & culture fit).
Diversity at Child Growth Monitor:
We are dedicated to creating an inclusive environment for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or caregiver status. We celebrate diversity and are committed to creating an inclusive environment for all employees. Diversity & Inclusion makes us better.
