MLOPS Data Science

13 hours ago

India Infogain Full time

Key Responsibilities:

  • Develop, train, and validate predictive and analytical models using machine learning techniques.
  • Collaborate with data engineers and business teams to define data requirements and success metrics.
  • Deploy machine learning models into production using ML Ops best practices.
  • Build automated pipelines for model training, testing, monitoring, and retraining.
  • Optimize model performance and ensure scalability and reliability.
  • Monitor model drift, performance degradation, and ensure continuous improvement.
  • Implement CI/CD practices for machine learning workflows.

Technical Skills Required:

  • Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
  • Experience with ML Ops tools/frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML).
  • Good understanding of data engineering concepts (ETL, data pipelines, APIs).
  • Hands-on with containerization and orchestration (Docker, Kubernetes).
  • Knowledge of cloud platforms (AWS, GCP, or Azure) for ML model deployment.
  • Strong background in statistics, machine learning algorithms, and model evaluation techniques .
  • Familiarity with version control (Git) and CI/CD pipelines.

Preferred Qualifications:

  • Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, or related field.
  • Experience in handling large-scale data pipelines and real-time model serving .
  • Exposure to feature stores and automated model monitoring.
  • Strong problem-solving, analytical, and communication skills.

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