Develop advanced computer vision and state-of-the-art deep learning-based applications for object detection classification sequence modeling, face recognition, scene understanding, and activity recognition.
Efficiently implement a module in Python targeting a specific architecture around the Deep Learning domain.
Hardware architecture aware and computation conscious implementation of solutions in an embedded device and maximizing the throughput.
Mentor fresh joiners and foster team culture.
B Tech/MS/MTech graduates in computer science, applied mathematics, electronics electrical engineering.

Solid programming experience with proven experience around computer vision problems.
Very good knowledge of advanced data structures and algorithms.
Experience in the development of computer vision and machine learning algorithms to solve challenging image understanding problems.
Proven ability to own and execute complex tasks, under tight schedules and dynamic conditions.
Experience in designing large complex systems with multiple services libraries spread across different hardware platforms like mobile, cloud, etc.

Good to have :

Experience in Deep Learning frameworks (like TensorFlow or Caffe or PyTorch) is a big plus.
Ability to translate customer requirements to determine research focus.
Strong communication skills and the ability to describe complex technical concepts to fellow researchers as well as to non-technical people.
Product development experience is a plus.
Experience with serving versioned ML models.
Benchmarking and Optimization experience for a specific architecture.
Experience with designing web services, API design versioning.