Information Systems Engineer

Short Description

Should be able to independently work with Deep Learning models related to computer vision like CNNs, generative models etc. Maintain a good overview understanding of latest architecture models (E.g. GANs, very deep / wide / dense / gated / skip models), algorithm trends (e.g. Adam) and techniques (e.g. for regularization or initialization) in deep-learning for computer-vision and judge their relevance to solve enterprise use-cases.

Job Description

Education And Qualifications / Skills And Competencies
  • Doctoral, Master's or Bachelor's degree in Engineering or Technology, majoring in Computer Science, from a reputed institute, with excellent academic records.
  • Hands-on experience with at least one major deeplearning library for computer-vision like  TensorFlow Torch or Theano.
  • Should be proficient in python and specifically in libraries used for machine-learning / computer-vision like openCV, numpy, scikit-learn, keras, matplotlib and scipy.
  • Ability to decipher the mathematical basis of machinelearning / deep-learning models based on linear-algebra, probability & statistics, vector / tensor algebra and calculus will be an added advantage, but is not mandatory.
  • Hands-on experience with scalable & parallelizable scripting algorithms that cater to large-scale image and video datasets used in conjunction with deep-learning for computer-vision.
  • Strong analytical and problem solving skills.
  • Goal-oriented team player with flexible mindset
  • Good communication skills, fluent in English, both written and spoken.

EXPECTATIONS AND TASKS
  • Should be able to independently work with Deep Learning models related to computer vision like CNNs, generative models etc.
  • Maintain a good overview understanding of latest architecture models (E.g. GANs, very deep / wide / dense / gated / skip models), algorithm trends (e.g. Adam) and techniques (e.g. for regularization or initialization) in deep-learning for computer-vision and judge their relevance to solve enterprise use-cases.
  • Should be able to rapidly develop, deploy, test and iterate with such architectural models / algorithms based on both inhouse and open-source research (concept-to-code) and guide the team to select the best approach for productive deployments.
  • Own the training life-cycle of deep-leaning based computervision models, including data-set preprocessing, augmentation, annotation tools and techniques, rapid iterations for hyper-parameter setting, interpretation of test result matrices and plots, fine-tuning and optimization.
  • Maintain an overview understanding of a deep learning technology stack from GPU based H/W through cuda / cudnn to framework implementation (in c++ or python) and use this know-how for optimizing the training and prediction workloads, dependency handling and performance tuning.
  • Brings hands-on flavor to all aspects in software engineering related to enterprise grade deep-learning.
  • Should be a good learner who takes initiative to drive topics to completion with a high quality, reliability and efficiency.

Work Experience
  • 4 - 8 years professional experience with at least 2 years of hands-on experience in deep learning, preferably with computer vision in an enterprise product development setting, in the role of a data scientist / deep learning senior engineer.
  • Experience in working with 3rd party tools and open source libraries relevant for the field of computer vision.
  • Contribution to open source community, participation in competitions (like Kaggle), certifications, paper publishing and presentations in relevant journals / conferences / events / meet-ups will be considered as additional merit.
  • Prior experience in working with Agile software methodologies (Scrum) and iterative development cycles for deep learning

Information Systems Engineer
Associate Computer Full-time Engineering | Information Technology Deep Learning
As a market leader in enterprise application software, SAP (NYSE: SAP) helps companies of all sizes and industries run better. From back office to boardroom, warehouse to storefront, desktop to mobile devices, SAP empowers people and organizations to work together more efficiently and use business insight more effectively to stay ahead of the competition. SAP applications and services enable more than 296,000 customers in 190 countries to operate profitably, adapt continuously, and grow sustainably.