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Machine Learning Engineer

Experience

3-5 years

Location

Sector-68, Noida

Job Description

Individual contributor
  • Understand Software/System components and associated specifications.
  • Ability to modify the architecture to enhance accuracy using different techniques like hyper parameter tuning, changing validation and test strategy, choosing right loss and activation functions.
  • Decent understanding of CNN based popular models like ResNet, BERT, VGG16 etc.
  • Apply statistical techniques for data analysis.
  • Optimization of neural architecture for production deployment.
Technical Skills
  • Good knowledge of Maths and Statistics particularly in the areas of calculus, linear algebra, and Bayesian statistics.
  • Working knowledge of CNN based architecture on imaging or video applications.
  • Good understanding of programming languages like Python, C/C++.
  • Good understanding of Tensorflow/Keras APIs.
  • Good understanding of OpenCV library.
  • Good understanding of various optimization techniques for production deployment.
  • Demonstratable track record of delivering on production environment.
  • Image processing/audio signal processing exposure is a plus.
  • Hands-on knowledge of using GPUs for tensorflow for speeding up inference.

 

Soft Skills
  • Strong analytical and problem-solving abilities, with quick adaptation to new technologies, methodologies, and systems.
  • Self-starter, having positive attitude, ability to proactively identify issues and/or opportunities for improvement
  • Mature, ability to understand business perspective of requirements and interpersonal relationships when interacting with non-team members
  • Team player
Qualification
  • Graduate/Post-Graduate in Computer Science/Maths/Stats/Physics from reputed institution
  • Consistently good academic record having minimum 70% throughout (10th std onwards)

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    Following information is required in the candidate’s resume

    • Complete academic information:
      – Board (for 10th and 12th)
      – College and university name (from where completed professional degree)
      – Percentage marks obtained, Year of passing
    • Duration of employment in the company/companies in which the candidate has worked
    • Project(s) worked on during employment
      – Duration of each of the project(s) which are published in the resume.
      – Role of the candidate in the project
      – Technologies and programming languages involved in the project
      – Team Size
    • Reason for gap in education and/or jobs if any.
    • Current CTC and expected CTC
    • Date of birth
    • Reason(s) for leaving the current job