About the role
Role Summary We are looking for a mid-level Python Developer 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 Responsibilities
* Develop and optimize ETL/data processing jobs using PySpark, Pandas, PyArrow, and related libraries. * 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.
Required Skills
* 10–12 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. * 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.
Nice-to-Have
* 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
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Job Family:
Applications Development
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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