Data Engineer for AI/ML

2 months ago


India Dhira Full time

Responsibilities

  • Develop and maintain APIs using Flask and Fast API frameworks to support AI/ML services, including data access, transformation, and integration with Large Language Models (LLMs).
  • Design and implement ETL processes to manage data pipelines and build Data Warehouses (DW) for efficient data storage and retrieval.
  • Work on integrating LLMs with API services, ensuring secure and efficient data flow and model interaction.
  • Develop APIs that abstract and conceal LLM functionality, providing a seamless interface for applications to interact with AI/ML models.
  • Collaborate with database systems to handle data manipulation, storage, and retrieval, supporting API-driven machine learning workflows.
  • Optimize Python code for performance and security, ensuring robust and scalable API deployment.
  • Participate in cross-functional team discussions to align technical solutions with business objectives.
  • Stay abreast of advancements in AI, machine learning, and software development practices to suggest and implement improvements.
  • Research and develop new algorithms to improve AI system performance.
  • Collaborate with cross-functional teams to integrate AI models and technologies into scalable products.  


Key Qualifications

  • Strong proficiency in Python with 6 years of experience in developing APIs.
  • Expertise in Flask and Fast API for API development.
  • Solid understanding of ETL processes, Data Warehousing, and working with relational databases such as PostgreSQL or MySQL.
  • Experience with integrating and managing Large Language Models (LLMs) and concealing their APIs behind custom-built services.
  • Knowledge of data transformation and access techniques to effectively feed AI/ML models.
  • Familiarity with Machine Learning development is advantageous but not essential.


Desired Traits

  • Strong problem-solving skills with a focus on optimizing API performance and ensuring security.
  • Ability to work both independently and collaboratively within a team.
  • Effective communication skills to explain technical concepts clearly and concisely.
  • Cloud computing: Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Big data technologies: Experience with big data tools and technologies such as Spark or similar.
  • Natural language processing (NLP): Knowledge of NLP techniques and applications.
  • Computer vision: Understanding of computer vision algorithms and applications


Educational Background

Bachelor’s degree in computer science, Information Technology, or a related field.



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