Responsibilities:
- Work Actively as a part of the Computer Vision and Deep Learning Team to Train Computer Vision Models
- Work Closely with the Data Science Team for Appropriate Dataset Curation
- Work on Challenging Problem Statements to fine-tune models with Huge Dataset
- Implementation of the SOTA Architectures for Model Training
- Work closely with the R&D Team towards improving model accuracy and precision for CCTV cameras
Requirements:
- Proficient with Training of Detection/Classification/Segmentation Models with Tensorflow/PyTorch
- Good understanding of Dataset Quality for Computer Vision Applications.
- Strong understanding of Model Training Dynamics. Should be able to find out the error and resolve it based on training/eval metrics.
- Good Theoretical and Practical Knowledge with the fundamentals of Deep Learning, eg. CNNs, Regularization Techniques, etc.
- Familiarity with State-of-the-Art Models like YOLO-series, Efficient Net/EfficientDet, etc.
- Experience with using Docker containers for Computer Vision/Deep Learning.
How we work:
- We use Microsoft Teams for daily communication, conduct daily standups and team meetings over Teams.
- We value open discussion, ownership, and a founder mindset.
- We prioritize design, amazing UI/UX, documentation, to-do lists, and data-based decision-making.
- We encourage team bonding through bi-weekly town halls, destressing sessions with a certified healer, and fun company retreats twice a year.
- We offer a 100% remote workplace model, health insurance, top performers eligible for attractive equity options, mental health consultations, company-sponsored upskilling courses, growth hours, the chance to give back with 40 hours for community causes, and access to a financial advisor.
- Wobot is an Equal Opportunity Employer
If you have a passion for developing innovative computer vision solutions and want to work on cutting-edge technology, we encourage you to apply for this exciting opportunity.