AI/ML Data Engineer
2 months ago
About Solytics Partners :
We are a company that utilizes AI/ML and cutting-edge technology to develop next-generation solutions and provide efficient services to BFSI and Healthcare firms. Our team consists of PHDs in AI/ML and experts in BFSI, and healthcare industry. Our solutions are regulatory compliant, enabling leading corporations and institutions to create and sustain competitive advantage.
Job Summary :
We are seeking an experienced AI/ML Data Engineer with 5+ years of hands-on experience in developing and implementing AI and machine learning use cases. The ideal candidate will possess strong programming skills in Python and have a passion for leveraging data to solve complex problems in the banking and fintech domain. This role focuses on data preparation, pipeline creation, and ensuring data accessibility for AI/ML initiatives.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines that support the ingestion and processing of large datasets for AI/ML applications.
- Collaborate with data scientists and business stakeholders to identify and define AI/ML use cases that drive value.
- Clean, preprocess, and transform raw data into structured formats suitable for analysis and machine learning tasks.
- Work closely with data scientists to ensure data is optimized for AI/ML use cases.
- Ensure data quality, integrity, and availability for AI/ML initiatives.
- Conduct exploratory data analysis to inform model development and feature engineering.
- Optimize machine learning models for performance and scalability, utilizing best practices in model evaluation and selection.
- Monitor data pipelines and AI/ML processes to ensure reliability and performance.
- Troubleshoot and resolve data-related issues, ensuring data integrity throughout the pipeline.
Requirements :
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
- 5+ years of experience as a Data Engineer, with a strong focus on AI/ML applications.
- Proficiency in Python for data manipulation and processing.
- Experience with data pipeline tools (e.g., Apache Airflow, Luigi, or similar).
- Solid understanding of data architecture, data modelling, and ETL processes.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
- Experience in the banking or fintech industry is highly desirable.
- Knowledge of SQL and NoSQL databases for data querying and management.
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) is a plus, but not required.
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