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1 Week ago

Back-End Developer – AI-Driven Data Remediation Department

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Bangalore, Karnataka, India
Information Technology
Full-Time
algoleap

Overview

Job Summary

We are looking for a Back-End Developer to build an AI-driven prescriptive remediation model for SuperZoom, CBRE’s data quality platform. This model will analyze invalid records flagged by data quality rules and attempt to suggest corrected values based on historical patterns. The model should also learn from past corrections to improve future recommendations. The ideal candidate has experience with machine learning, NLP, data quality, and backend development.

Key Responsibilities

  • Develop a prescriptive remediation model to analyze bad records and suggest corrections.
  • Implement a feedback loop where the model learns from past incorrect and corrected values.
  • Build APIs and backend workflows to integrate the remediation model into SuperZoom.
  • Design a data pipeline that processes flagged records and suggests fixes in real-time.
  • Optimize model performance for large-scale datasets and ensure accuracy of predictions.
  • Collaborate with data governance teams, data scientists, and front-end developers.
  • Ensure security, scalability, and performance in handling sensitive data.

Required Skills & Experience

  • 5+ years of backend development experience, with a focus on AI/ML-driven solutions.
  • Strong Python skills, including experience with Pandas, PySpark, and NumPy.
  • Experience with machine learning libraries such as Scikit-Learn, TensorFlow, or Hugging Face Transformers.
  • Solid understanding of data quality, fuzzy matching, and NLP techniques for text correction.
  • Proficiency in SQL and working with PostgreSQL, Snowflake, or MS SQL Server.
  • Experience building RESTful APIs and integrating ML models into production systems.
  • Strong problem-solving and analytical skills for handling diverse data quality issues.

Nice-to-Have Skills

  • Experience with vector databases (e.g., Pinecone, Weaviate) for similarity search.
  • Familiarity with LLMs and fine-tuning for data correction tasks.
  • Experience with Apache Airflow for workflow automation.
  • Knowledge of reinforcement learning to improve remediation accuracy over time.

Success Metrics

  • Accurate and relevant suggestions for data quality issues in flagged records.
  • Improved model performance through iterative learning from bad and corrected values.
  • Seamless integration of the remediation model into Super Zoom.
  • On-time delivery of backend features in coordination with the data governance team.
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