AI Engineer

Responsibilities:

• Design and develop scalable, flexible, and efficient data pipelines for data preparation, feature extraction, training, and inference, integrated with the AI Platform.
• Implement MLOps practices to support the model lifecycle, including data versioning, model tracking, CI/CD pipelines, deployment, and monitoring.
• Research and select appropriate Cloud and AI-related services (e.g., LLMs, image processing, document processing) tailored to specific use cases.
• Develop AI solutions that reduce the need for frequent retraining of Foundation Models by applying advanced techniques such as RLHF.
• Regularly audit AI models for security, reliability, stability, and accuracy.
• Create and manage technical documentation, user guides, and operational guidelines for AI system maintenance.
• Review and enhance code quality, integration testing, and collaborate with QA to maintain system stability.
• Collaborate with Application, Data Platform, and Product teams to integrate AI solutions into existing systems.
• Stay up to date with emerging technologies in AI, MLOps, Cloud, DevOps, and industry best practices.
• Evaluate third-party tools, frameworks, and platforms to enhance AI development efficiency.
• Support internal teams and clients in understanding and adopting the AI Platform.

Qualifications:

• Bachelor's or Master’s in Computer Science, Artificial Intelligence, or a related field.
• Extensive experience in designing AI applications and knowledge of machine learning frameworks like Tensor Flow or PyTorch.
• Proven ability to lead and manage projects with cross-functional teams.
• Strong communication skills to effectively collaborate with various stakeholders.
• Critical thinking and problem-solving skills are essential.
• Experience with ethical AI practices and ensuring compliance with data protection regulations.
• At least 2-5 years of experience in AI work.