Deep Learning Engineer

Responsibilities

• Work with machine learning & deep learning experts to design and implement algorithms/ networks optimized for GPU-accelerated inference
• Development of standard or customized model for image classification, segmentation, object detection and localization
• Implementation of MLOPS operations such as data acquisition, data preprocessing, model building, model retraining and monitoring of model
• Coordinating with front end team to display the AI results and reports
• Model development for structured/tabular data
• Use of Jenkins for project deployment and unit testing

Experience

• A minimum of 3 years of relevant experience in a similar role

Qualification

• Bachelor of Engineering (B. Tech / BE) or Masters (M. Tech / MS / MCA) in Computer Science / Information Science or Ph. D in Computer Science / Information Science

Skills Required

Essential

• Excellent in machine learning and deep learning concepts such as
  • Data understanding and analysis
  • Supervised, Unsupervised, Semi-supervised learning techniques
  • CNN and RNN
• Excellent in Python programming
• Clear understanding and hands on experience of using computer vision and machine learning libraries such as Tensorflow, PySpark, Torch & Caffe
• Good unit testing either using Unit test / Nose2 / Pytest
• Experience in creating APIs like REST
• Good coding documentation skills
• Good knowledge on problem solving, data structure and databases
• Good communication skills to communicate ideas and issues to the team

Additional Skill sets

• Good knowledge in C/C++
• Hands on experience of using spark in clusters
• Experience using GPU-accelerated libraries (e.g., cuDNN and cuBLAS)
• Experience with code generation & optimization
• Exposure to Jenkins deployment with integration of unit testing packages