Data Engineer for AI/ML

1 week ago

India Dhira Full time

Responsibilities

· Develop and maintain APIs using Flask and FastAPI 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 FastAPI 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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