Sharechat work from home career recruitment 2023|machine learning Engineer|6.5LPA|apply soon

Sharechat work from home jobs for freshers 2022|machine learning Engineer|work from home|6.5LPA|apply soon

Sharechat recruitment 2022 :

  • Company – sharechat
  • Role – machine learning Engineer
  • Salary – 6.5 LPA
  • Experience – 0-2 years
  • Location – work from home
  • Batch – 2023/2022 /2021 /2020 /2019 /2018
  • Qualification – bachelors degree |masters degree

Job description :

  • Building out feature computation, storage, monitoring, analysis and serving systems for billions of features required across ShareChat applications every day
  • Developing distributed real-time training & experiment infrastructure over terabytes of data
  • Developing a highly scalable, high-QPS inference service providing low latency performance using a mix of CPU and GPU hardware to most efficiently utilise resources
  • Scaling distributed backend services to reliably support high-QPS low latency use cases
  • Building core data and model metadata systems powering the end-to-end ML lifecycle
  • Advancing the usage of ML monitoring, observability and explainability across the company

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Skills required :

  • Strong coding skills with Go, Java or Scala. Familiarity with Python is a plus.
  • Hands-on experience using data processing tools like Beam, Spark or Flink in a cloud environment like GCP or AWS and first-hand knowledge about data management concepts
  • Written libraries or tools used by other engineers or researchers.
  • A keen drive for code quality, reliability, continuous improvement and monitoring.
  • Value for team success over personal success
  • Experience developing and productionising machine learning models is a plus
  • Industry experience building end-to-end Machine Learning Infrastructure a big plus
  • Experience with Docker, Kubernetes or Flink is a plus
  • You have a preference for working in an end-to-end product development flow: from user research, discovery, coding and testing to deployment, monitoring and gathering feedback.
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