Coforge - Machine Learning Engineer - PySpark/Python

3 weeks ago

Gurugram, India COFORGE Full time

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.

(ref:hirist.tech)

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