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Job Type

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Job Description

Data Platform Engineering Team is responsible for Building Data platfrom for enterprise The MLenablement team has a combination of data engineers, machine learning engineers (MLEs). MLEs wouldbe supposed to implement sophisticated machine learning models that can transform DPE.

Responsibilities

  • Build Deep learning models to understand and derive insights from data (Multi-modal - text, image, audio, etc.)
  • Develop custom transformer architectures to solve business problems.
  • Understand business needs and come up with an appropriate solution architecture for the use-case
  • Ensure deployment of ML models into production by working closely with data engineers / ML-Ops engineers.
  • Use of test-driven Development and code pairing practices (version control).
  • Collaborate with other product teams on integrations, testing and deployments..

Qualifications

  • 4 – 7 years of overall experience in machine learning with proven experience in deep learning model training and deployment
  • 2+ Years of strong hands-on experience in PyTorch, Hugging face and good understanding of optimizers, learning rate schedulers, etc. Experience in distributed GPU compute is preferable.
  • 4+ years of hands-on experience with Python programming language.
  • Ability to work well in a collaborative, agile development team with business and development partners.
  • Strong team player who is willing to learn, share, teach and lead depending on the situation.
  • Excellent problem-solving and communication skills
  • Good to have!
  • Continuously integrate and deploy developed software; modify CI/CD pipeline and scripts as necessary to improve continuous integration practices (Terraform).
  • Experience in Google Cloud Platform (GCS, Big Query, Cloud Run, Cloud Build, Pub/Sub)

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