Coforge - Machine Learning Engineer - PySpark/Python
2 weeks ago
Responsibilities :
Model Deployment & Management :
- Ensure seamless operation of deployed machine learning models within the RCP platform.
- Monitor and troubleshoot model performance for accuracy and efficiency.
- Collaborate with data scientists and software engineers to optimize model pipelines for production.
Machine Learning Operations (MLOps) :
- Utilize Airflow to schedule and orchestrate the execution of machine learning pipelines, ensuring timely and efficient processing.
- Develop and implement logging strategies to capture application and Airflow logs for monitoring and analysis.
- Design and maintain workflows for MLOps processes within the team.
Data Engineering & Integration :
- Utilize PySpark for handling the complete data flow, including data cleaning, transformation, and feature engineering for machine learning models.
- Integrate various data sources and services within the machine learning pipelines.
Technical Expertise :
- Leverage Python and PySpark as your primary tools for data manipulation and machine learning development.
- Utilize Spark Streaming for real-time processing of data streams.
- Possess a working knowledge of AWS cloud platform, Docker containers, and Kubernetes for potential deployments.
Problem-Solving & Communication :
- Debug and troubleshoot issues that arise during the execution of machine learning pipelines.
- Collaborate effectively with data scientists, software engineers, and platform operations teams to resolve challenges and optimize solutions.
- Document technical processes and findings clearly.
Qualifications :
- 4-8 years of experience as a Machine Learning Engineer or related field.
- Strong understanding of machine learning concepts, algorithms, and methodologies.
- Expertise in Python and PySpark for data analysis and machine learning development.
- Experience with Airflow for scheduling and orchestrating machine learning pipelines.
- Familiarity with MLOps principles and practices for model deployment and management.
- Experience integrating different data sources and services within machine learning pipelines.
- Strong problem-solving and debugging skills.
- Excellent communication and collaboration skills.
Bonus Points :
- Experience working with AWS, Docker, and Kubernetes technologies.
- Experience in a travel technology or hospitality domain.
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