Machine Learning Model Developer

4 days ago


Palakkad, Kerala, India beBeeMLOPS Full time ₹ 15,00,000 - ₹ 25,00,000
Machine Learning Operations (MLOPS) Specialist Position

Mission Overview:

  • We seek a highly skilled MLOPS Specialist to drive business value by developing, deploying, and maintaining machine learning models.

Key Responsibilities:

  • Develop predictive and analytical models using machine learning techniques and train them on large datasets.
  • Collaborate with data engineers and business teams to define data requirements and success metrics for model deployment.
  • Deploy ML models into production using industry best practices such as continuous integration/continuous delivery (CI/CD).
  • Design automated pipelines for model training, testing, monitoring, and retraining to ensure model performance and scalability.
  • Optimize model performance, handle model drift, and ensure continuous improvement of machine learning workflows.
  • Implement CI/CD practices and version control systems for reproducibility and collaboration.

Technical Skills Required:

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

Job Requirements:

  • Develop and maintain high-quality machine learning models that meet business needs.
  • Collaborate with cross-functional teams to integrate ML models into production environments.
  • Design and implement automated pipelines for model training, testing, and deployment.
  • Optimize model performance and ensure scalability, reliability, and continuous improvement.
  • Stay up-to-date with industry trends and advancements in machine learning and MLOPS.

Benefits:

  • Competitive salary and benefits package.
  • Opportunities for professional growth and development.
  • Collaborative and dynamic work environment.


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