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AI / ML

AI / ML

CozzeraJaipur, IN
6 days ago
Job description

Job Title : AI / ML Developer (Remote)

Experience Required : 5 Years

Location : Remote (India-based preferred)

Employment Type : Full-Time

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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