22 Oct
Dhira
Gandhinagar
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.
▶️ Data Engineer for AI/ML
🖊️ Dhira
📍 Gandhinagar