Senior Data Engineer: AI/ML Expert

1 month ago


Pune, Maharashtra, India Solytics Partners Full time

About Solytics Partners :

We are a leading provider of innovative AI and machine learning solutions to BFSI and Healthcare firms. Our team of experts uses cutting-edge technology to develop next-generation solutions and services that drive value for our clients.

Job Overview :

We are seeking an experienced AI/ML Data Engineer to join our team. The ideal candidate will have 5+ years of hands-on experience in developing and implementing AI and machine learning use cases, with strong programming skills in Python and a passion for leveraging data to solve complex problems in the banking and fintech domain.

Key Responsibilities :

  1. Design, develop, and maintain scalable data pipelines that support the ingestion and processing of large datasets for AI/ML applications.
  2. Collaborate with data scientists and business stakeholders to identify and define AI/ML use cases that drive value.
  3. Clean, preprocess, and transform raw data into structured formats suitable for analysis and machine learning tasks.
  4. Work closely with data scientists to ensure data is optimized for AI/ML use cases.
  5. Ensure data quality, integrity, and availability for AI/ML initiatives.
  6. Conduct exploratory data analysis to inform model development and feature engineering.
  7. Optimize machine learning models for performance and scalability, utilizing best practices in model evaluation and selection.
  8. Monitor data pipelines and AI/ML processes to ensure reliability and performance.
  9. Troubleshoot and resolve data-related issues, ensuring data integrity throughout the pipeline.

Requirements :

  1. Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
  2. 5+ years of experience as a Data Engineer, with a strong focus on AI/ML applications.
  3. Proficiency in Python for data manipulation and processing.
  4. Experience with data pipeline tools (e.g., Apache Airflow, Luigi, or similar).
  5. Solid understanding of data architecture, data modelling, and ETL processes.
  6. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
  7. Experience in the banking or fintech industry is highly desirable.
  8. Knowledge of SQL and NoSQL databases for data querying and management.
  9. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) is a plus, but not required.


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