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Machine Learning Engineer II - Backend

3 - 5 years

11 - 15 Lacs

bengaluru

Posted:2 weeks ago| Platform: Naukri logo

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Skills Required

computer science accessories architecture coding gcp machine learning agile monitoring sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

  • Model Development & Deployment

  • Design, train, and deploy machine learning models with a strong focus on fast, reliable experimentation.
  • Build APIs and microservices to serve ML models at scale.
  • Feature development & Engineering
  • Design & deliver asks on backend features & efficiently deliver features.
  • Work closely with the analytics, architects & PM to deliver features asks as per ETA.
  • Identify solutions that can help us improve scalability, minimize bugs and reduce cost
  • Understanding of when to escalate questions/issues that arise during development
  • Able to efficiently diagnose bugs and issues
  • Familiar with various design and architectural patterns

  • Pipeline & Infrastructure

  • Develop and maintain data ingestion, preprocessing, and model training pipelines.
  • Deploy scalable data and model solutions that improve efficiency across ML workflows.

  • Collaboration & Integration

  • Work closely with
  • Define and execute end-to-end ML solutions from ideation to production.

  • Monitoring & Research

  • Monitor model performance in production, using statistical methods to ensure robustness.

  • Ownership & Delivery

  • Lead or contribute to POCs and full-scale ML feature rollouts.
  • Manage project deadlines and deliverables in an agile environment.

Basic Qualifications

  • Bachelors degree with 4+ years OR Masters degree with 3+ years in Computer Science, Machine Learning, Data Science, or related field.
  • Proven experience in developing and deploying ML models in production.
  • Strong proficiency in

    Python

    and ML libraries like

    TensorFlow

    ,

    PyTorch

    , or

    scikit-learn, spark, java & distributed systems.

  • Understanding of statistical methods and hypothesis testing.
  • Comfortable working with structured and unstructured data.
  • Experience working in collaborative, cross-functional teams.
  • Loves to code and learn new concepts, technologies and frameworks

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