Description

You'll be responsible for (Responsibilities):

  • Lead data curation, feature engineering, and EDA, preparing datasets for model development.
  • Implement scalable AI/ML models and MLOps pipelines, covering the end-to-end model lifecycle.
  • Collaborate with cross-functional teams to align AI solutions with business and data requirements.

You'll have (Qualification & Experience): 

  • Bachelor’s or Master’s degree in Computer Science, AI, or related field.
  • 3–6 years in software engineering, with at least 3 years in AI/ML and data engineering.
  • Programming: Strong skills in Python, R, or similar, for robust data handling and model customization.
  • Data Engineering: Proficient in data curation, EDA, feature engineering, and data transformation techniques.
  • ML Frameworks: Proficiency with TensorFlow, PyTorch, or similar frameworks.
  • MLOps and Cloud Integration: Familiarity with MLOps tools (e.g., MLflow, Kubeflow) and cloud platforms (AWS, Azure, GCP).
  • Big Data: Working knowledge of ETL processes, SQL, and big data tools like Spark or Databricks.

Nice to Have:

  • Proficiency in Dataiku, Databricks, or similar tools.
  • Experience in model optimization and hyperparameter tuning


 

Key Skills
Education

Any Graduate

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