Machine Learning Engineer
Key Responsibilities:
• Develop and deploy scalable data pipelines and machine learning models to support operational efficiency.
• Utilize Python and SQL for data processing, with a preference for experience in PySpark and Databricks.
• Ensure seamless integration of machine learning models into production environments, maintaining reliability and scalability.
• Build and maintain data pipelines for ingesting, transforming, and storing large datasets.
• Develop backend infrastructure to support machine learning and AI-driven solutions.
• Automate machine learning model pipelines, ensuring efficient deployment and monitoring.
• Work closely with data scientists to enhance model performance and scalability.
Basic Qualifications:
• Proficiency in Python and SQL, with hands-on experience in developing data pipelines and deploying machine learning models.
• Strong analytical and problem-solving skills, with the ability to conduct complex independent analyses.
• Excellent communication and interpersonal skills, both verbal and written.
• Ability to manage multiple projects and meet deadlines effectively.
• Experience using data visualization tools such as Tableau or Power BI.
• Familiarity with machine learning frameworks like TensorFlow and PyTorch.
Preferred Qualifications:
• Bachelor’s and/or Master’s degree in analytics, computer science, or a related field.
• Years of experience in machine learning and optimization.
• Experience in managing the machine learning lifecycle and operationalization.
• Knowledge of deep learning techniques and implementation.
• Experience with cloud platforms such as AWS, Azure, or GCP, along with CI/CD tools like Jenkins or GitLab CI.
• Hands-on experience with PySpark and Databricks.
• Understanding of railway measurement systems and reporting tools (e.g., DPR, SCORE, Corporate Dashboard).
Key Responsibilities:
• Develop and deploy scalable data pipelines and machine learning models to support operational efficiency.
• Utilize Python and SQL for data processing, with a preference for experience in PySpark and Databricks.
• Ensure seamless integration of machine learning models into production environments, maintaining reliability and scalability.
• Build and maintain data pipelines for ingesting, transforming, and storing large datasets.
• Develop backend infrastructure to support machine learning and AI-driven solutions.
• Automate machine learning model pipelines, ensuring efficient deployment and monitoring.
• Work closely with data scientists to enhance model performance and scalability.
Basic Qualifications:
• Proficiency in Python and SQL, with hands-on experience in developing data pipelines and deploying machine learning models.
• Strong analytical and problem-solving skills, with the ability to conduct complex independent analyses.
• Excellent communication and interpersonal skills, both verbal and written.
• Ability to manage multiple projects and meet deadlines effectively.
• Experience using data visualization tools such as Tableau or Power BI.
• Familiarity with machine learning frameworks like TensorFlow and PyTorch.
Preferred Qualifications:
• Bachelor’s and/or Master’s degree in analytics, computer science, or a related field.
• Years of experience in machine learning and optimization.
• Experience in managing the machine learning lifecycle and operationalization.
• Knowledge of deep learning techniques and implementation.
• Experience with cloud platforms such as AWS, Azure, or GCP, along with CI/CD tools like Jenkins or GitLab CI.
• Hands-on experience with PySpark and Databricks.
• Understanding of railway measurement systems and reporting tools (e.g., DPR, SCORE, Corporate Dashboard).
