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Job Description
Structured overview of role & requirementsAbout This Role
Develop and optimize large-scale data processing and ETL pipelines using PySpark, Pandas, and PyArrow.
Build and maintain NLP pipelines leveraging Flair, BERT, HuggingFace Transformers, and related LLM frameworks.
Develop and maintain Flask-based APIs for model inference, integrate services, and manage deployment using CI/CD pipelines and tools like MLflow and Autosys.
Minimum Requirements
10–12 years of hands-on Python programming experience with strong OOP and design patterns knowledge.
Experience in NLP frameworks including Flair, BERT, and HuggingFace Transformers, plus data engineering tools like PySpark and Pandas.
Proficiency with API development using Flask, MLflow for model deployment, Autosys for job scheduling, and familiarity with Linux commands and shell scripting.
Work Experience Required: 10-12 years as explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in building scalable, distributed data and NLP pipelines for AI/analytics use cases with strong Python expertise.
Familiar with end-to-end deployment including API service integration, model versioning, CI/CD practices, and monitoring tools in production environments.
Comfortable working with cloud services (notably AWS boto3), in-memory data stores like Redis, and scheduling/automation tools, indicating capability to manage complex data workflows and deployments.