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5 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Job Title:

Experience Required:

Location:

Employment Type:


About the Role:

We are looking for a skilled and motivated AI/ML Developer with 5 years of hands-on experience in building and deploying machine learning solutions. You will work with cross-functional teams to deliver cutting-edge AI applications that solve real-world problems. This is a remote role offering flexibility and the chance to work with a fast-paced, innovation-driven team.


Key Responsibilities:

  • Design, develop, and deploy ML models for classification, regression, NLP, and/or computer vision tasks.
  • Collect, preprocess, and analyze large datasets.
  • Work with frameworks such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face.
  • Implement and optimize model training pipelines using Python.
  • Collaborate with product managers, data engineers, and backend teams to integrate ML models into production.
  • Continuously evaluate model performance and update them based on new data and requirements.
  • Write clean, maintainable, and well-documented code.
  • Stay current with the latest AI/ML trends and technologies.


Required Skills:

  • Strong programming skills in

    Python

    and hands-on experience with

    machine learning libraries

    (e.g., Scikit-learn, TensorFlow, PyTorch).
  • Proficiency in

    data handling and preprocessing

    using

    Pandas

    ,

    NumPy

    , and

    SQL

    .
  • Experience with

    model deployment tools

    (e.g., FastAPI, Flask, Docker, AWS/GCP).
  • Sound understanding of

    ML algorithms

    , model evaluation metrics, and tuning techniques.
  • Practical experience in

    NLP

    ,

    Computer Vision

    , or

    Recommendation Systems

    is a plus.
  • Experience with

    version control systems

    like Git and CI/CD pipelines.


Good to Have:

  • Experience working in a

    remote team environment

    .
  • Exposure to

    MLOps tools

    such as MLflow, Kubeflow, or Vertex AI.
  • Familiarity with

    big data tools

    like Spark or Hadoop.
  • Prior work on

    production-grade ML pipelines

    .

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