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Role Summary
We are looking for a mid-level Python Developer with combined experience in Data Engineering andAI/NLP engineering. The candidate will build NLP pipelines using libraries such as Flair, BERT, and LLM frameworks, and will also work on large-scale data processing using PySpark, Pandas, and related data tools. The role includes developing APIs, integrating with platform services, and supporting CI/CD deployments using GitHub and LightSpeed Enterprise.
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Develop and optimize ETL/data processing jobs using PySpark, Pandas, PyArrow, and related libraries.
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Work with Parquet files using FastParquet or pyarrow.parquet for efficient data processing.
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Implement data parsing and serialization using json, ujson, or orjson for high-performance JSON handling.
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Build and maintain NLP pipelines using Flair, BERT, and LLM-based models.
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Develop scalable ingestion and data transformation pipelines for AI and analytics use cases.
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Build and maintain Flask-based APIs for model inference and service integrations.
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Use regular expressions for text cleaning, parsing, and NLP preprocessing.
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Integrate caching and fast lookups using Redis.
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Manage and deploy ML models using MLflow for tracking and versioning.
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Support CI/CD workflows using GitHub, LightSpeed Enterprise, and deployment pipelines.
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Create and maintain Autosys JILs for job scheduling and automation.
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Use basic Linux commands for troubleshooting, operations, and deployment tasks.
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Monitor application and system health using ITRS Geneos.
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Write unit tests and improve automation test coverage (PyTest/unittest).
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Work with REST APIs, microservices, and basic shell scripting.
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Work with cloud services (ECS), including boto3.
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8+ years of hands-on Python programming experience.
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Strong fundamentals in Python, OOP, and design patterns.
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Experience with NLP libraries such as Flair, BERT, HuggingFace Transformers, or similar.
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Solid experience with PySpark, Pandas, PyArrow, and distributed data pipelines.
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Proficient in working with Parquet using FastParquet or pyarrow.parquet.
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Familiarity with fast JSON parsing libraries (json, ujson, orjson).
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Experience building APIs using Flask (FastAPI is a plus).
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Experience with MLflow for model tracking and deployment.
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Good understanding of CI/CD practices and Git workflows.
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Experience working with Redis or similar in-memory stores.
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Experience with Autosys JILs for job scheduling.
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Comfortable with Linux command line and shell scripting.
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Strong debugging, problem-solving, and teamwork skills.
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Exposure to cloud services; AWS boto3 experience is an asset.
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Experience with Polars or Dask for high-performance data processing.
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Experience with PyTorch or TensorFlow for model training.
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Experience with Docker, Kubernetes, or containerized deployments.
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Experience with monitoring tools such as ITRS Geneos.
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Experience with FastAPI, Airflow, or Prefect.
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Technology
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Applications Development
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Full time
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Please see the requirements listed above.
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For complementary skills, please see above and/or contact the recruiter.
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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
