Data Scientist Machine Learning Engineer

11 hours ago


Thāne, Maharashtra, India beBeeMachineLearning Full time

Job Title: Data Scientist Machine Learning Engineer

About the Role

We are seeking an experienced Data Scientist Machine Learning Engineer to join our team. The ideal candidate will have a strong background in machine learning, data engineering, and software development.

Key Responsibilities
  1. Develop, train, and validate predictive and analytical models using machine learning techniques.
  2. Collaborate with data engineers and business teams to define data requirements and success metrics.
  3. Deploy machine learning models into production using best practices.
  4. Build automated pipelines for model training, testing, monitoring, and retraining.
  5. Optimize model performance and ensure scalability and reliability.
  6. Monitor model drift, performance degradation, and ensure continuous improvement.
  7. Implement CI/CD practices for machine learning workflows.
Required Skills and Qualifications
  • 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.
About Us

We are a dynamic company dedicated to innovation and excellence. We offer a collaborative work environment, opportunities for growth and development, and a competitive compensation package.


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