Role Summary
We are looking for a mid-level Python Developer - NLP, ML, Gen AI with combined experience in Data Engineering and AI/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.
Key ResponsibilitiesDevelop and optimize ETL/data processing jobs using PySpark, Pandas, PyArrow, and related libraries.
Work with Parquet files using FastParquet or pyarrow.parquet for efficient data processing.
Implement data parsing and serialization using json, ujson, or orjson for high-performance JSON handling.
Build and maintain NLP pipelines using Flair, BERT, and LLM-based models.
Develop scalable ingestion and data transformation pipelines for AI and analytics use cases.
Build and maintain Flask-based APIs for model inference and service integrations.
Use regular expressions for text cleaning, parsing, and NLP preprocessing.
Integrate caching and fast lookups using Redis.
Manage and deploy ML models using MLflow for tracking and versioning.
Support CI/CD workflows using GitHub, LightSpeed Enterprise, and deployment pipelines.
Create and maintain Autosys JILs for job scheduling and automation.
Use basic Linux commands for troubleshooting, operations, and deployment tasks.
Monitor application and system health using ITRS Geneos.
Write unit tests and improve automation test coverage (PyTest/unittest).
Work with REST APIs, microservices, and basic shell scripting.
Work with cloud services (ECS), including boto3.
3–5 years of hands-on Python programming experience.
Strong fundamentals in Python, OOP, and design patterns.
Experience with NLP libraries such as Flair, BERT, HuggingFace Transformers, or similar.
Solid experience with PySpark, Pandas, PyArrow, and distributed data pipelines.
Proficient in working with Parquet using FastParquet or pyarrow.parquet.
Familiarity with fast JSON parsing libraries (json, ujson, orjson).
Experience building APIs using Flask (FastAPI is a plus).
Experience with MLflow for model tracking and deployment.
Good understanding of CI/CD practices and Git workflows.
Experience working with Redis or similar in-memory stores.
Experience with Autosys JILs for job scheduling.
Comfortable with Linux command line and shell scripting.
Strong debugging, problem-solving, and teamwork skills.
Exposure to cloud services; AWS boto3 experience is an asset.
Experience with Polars or Dask for high-performance data processing.
Experience with PyTorch or TensorFlow for model training.
Experience with Docker, Kubernetes, or containerized deployments.
Experience with monitoring tools such as ITRS Geneos.
Experience with FastAPI, Airflow, or Prefect.
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Job Family Group: Technology------------------------------------------------------
Job Family:Applications Development------------------------------------------------------
Time Type:Full time------------------------------------------------------
Primary Location Full Time Salary Range:$94,300.00 - $141,500.00------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
Automated Processing and AIWe use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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This job opening is for an existing job vacancy.
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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.
Skills Required
- 3-5 years of hands-on Python programming experience
- Experience with NLP libraries such as Flair, BERT, HuggingFace Transformers
- Solid experience with PySpark, Pandas, PyArrow, and distributed data pipelines
- Experience building APIs using Flask
- Experience with MLflow for model tracking and deployment
- Good understanding of CI/CD practices and Git workflows
- Experience working with Redis or similar in-memory stores
- Comfortable with Linux command line and shell scripting
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
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Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
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Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
Citi Insights
What We Do
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.
