Data Scientist MLOPS

5 days ago

Gulbarga, Karnataka, India beBeeMachineLearning Full time ₹ 15,00,000 - ₹ 20,00,000
MLOPS Data Scientist

Our ideal candidate will be responsible for developing, training, and validating predictive and analytical models using machine learning techniques. They will collaborate with data engineers and business teams to define data requirements and success metrics.

Key Responsibilities:

  • Data Science and Analytics: Develop, train, and validate predictive and analytical models using machine learning techniques.
  • Collaboration: Collaborate with data engineers and business teams to define data requirements and success metrics.
  • Model Deployment: Deploy machine learning models into production using ML Ops best practices.
  • Pipeline Management: Build automated pipelines for model training, testing, monitoring, and retraining.
  • Performance Optimization: Optimize model performance and ensure scalability and reliability.
  • Monitoring and Improvement: Monitor model drift, performance degradation, and ensure continuous improvement.
  • CICD Practices: Implement CICD practices for machine learning workflows.

Required Skills and Qualifications:

  • Programming Language: Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
  • ML Ops Tools/Frameworks: Experience with ML Ops tools/frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML).
  • Data Engineering Concepts: Good understanding of data engineering concepts (ETL, data pipelines, APIs).
  • Containerization/Orchestration: Hands-on with containerization and orchestration (Docker, Kubernetes).
  • Cloud Platforms: Knowledge of cloud platforms (AWS, GCP, or Azure) for ML model deployment.
  • Statistics/Machine Learning Algorithms: Strong background in statistics, machine learning algorithms, and model evaluation techniques.
  • Version Control/CICD Pipelines: Familiarity with version control (Git) and CI/CD pipelines.

Benefits:

  • Education: Bachelor's/Master's degree in Computer Science, Data Science, Statistics, or related field.
  • Experience: Experience in handling large-scale data pipelines and real-time model serving.
  • Feature Stores/Automated Model Monitoring: Exposure to feature stores and automated model monitoring.

We Offer:

  • A competitive salary and benefits package.
  • A dynamic and supportive work environment.
  • Opportunities for professional growth and development.

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