Gen AI Developer

Design and implement robust data pipelines to collect, process, and store large volumes of structured and unstructured data.

Data Integration: Collaborate with data scientists and AI teams to integrate data from various sources, ensuring data quality and accessibility for machine learning models.

Database Management: Manage and optimize databases and data warehouses to support data retrieval and analytics.

Data Modeling: Create and maintain data models that facilitate the effective analysis of data for AI applications.

Performance Tuning: Monitor and optimize the performance of data systems, ensuring efficient processing and storage.

Documentation: Document data engineering processes, architecture, and standards to ensure clarity and consistency.

Collaboration: Work closely with cross-functional teams to understand data requirements and translate them into technical specifications.

Education: Bachelor’s degree in Computer Science, Data Engineering, or a related field; Master’s degree preferred.

Experience: Minimum of 3 years of experience in data engineering, with a focus on AI and machine learning projects.

Technical Skills: Proficiency in data engineering tools and technologies (e.g., Apache Spark, Kafka, SQL, NoSQL databases), programming languages (e.g., Python, Java), and cloud platforms (e.g., AWS, Azure, GCP).

Data Modeling: Strong understanding of data modeling techniques and best practices.

ETL Processes: Experience with ETL (Extract, Transform, Load) processes and data integration techniques.

Analytical Skills: Strong analytical and problem-solving skills, with the ability to work with large datasets.

Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.

Experience with AI frameworks and tools (e.g., TensorFlow, PyTorch)

Knowledge of machine learning concepts and algorithms.

Knowledge of natural language processing (NLP) and computer vision techniques