Machine Learning Engineer, Ad Platforms


Job Overview

Key Qualifications

  • 3+ years relevant experience in in Algorithms, Artificial Intelligence, Distributed Systems, Machine Learning, Data Science or Statistics
  • Building language models, collaborative filtering and using cutting edge modeling techniques to solve hard Deep Learning problems
  • You should have experience in software development using a general purpose programming language (e.g., Python, Java, C/C++, C#, Objective-C, and/or Swift)
  • Previous experience working in any of the following: Privacy preserving machine learning algorithms such as Differential Privacy; Developing Risk models for Ad Fraud and Spam Detection; Developing Anomaly Detection models; Building deep representations based on language modeling & collaborative filtering; Developing audience segmentation models, attribution or lift models; Developing ML approaches, features for supporting search relevance & advertising performance
  • Ability to design and implement both independently and with larger teams
  • Closely working with operational teams on deployment, monitoring, model retrain and other aspects of MLOps
  • Experience in distributed machine learning architectures and/or federated learning
  • Any previous experience working with a public cloud infrastructure such as GCP, Azure or AWS is an added advantage
  • Description

    You will have the opportunity to work on a platform with extreme scale and performance requirements. You would be applying your skills to work across the stack to develop, test, deploy and maintain ML based software solutions. Develop machine learning models using relevant frameworks such as TensorFlow and PyTorch. Implement and adapt deep learning network architectures, such as CNN and RNN. You would participate in cutting edge research in artificial intelligence and machine learning applications.

    Education & Experience

    MS or PhD in Computer Science, Electrical Engineering or other STEM fieldsInterest and ability to invest in continual learning of new technical and soft skills

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