Generative AI Engineer III

Key Responsibilities

• Design, develop, and fine‑tune large generative AI models (e.g., diffusion, transformer‑based) for diverse business applications.
• Architect end‑to‑end data pipelines that ingest, preprocess, and serve training data at scale.
• Containerize model training and inference workloads using Docker and orchestrate them on Kubernetes clusters.
• Collaborate with data scientists and product teams to translate research prototypes into production‑ready services.
• Implement monitoring, logging, and automated CI/CD workflows to ensure model reliability and performance.

Requirements

• 5+ years of professional experience in AI/ML engineering, with a focus on generative models.
• Strong proficiency in Python and deep‑learning libraries such as TensorFlow or PyTorch.
• Hands‑on experience building and scaling data pipelines and deploying models in Docker/Kubernetes environments.
• Solid understanding of model optimization, distributed training, and cloud‑native best practices.
• Excellent problem‑solving skills and ability to work cross‑functionally in fast‑paced teams.