Job Responsibilities :
- Design, implement, and manage scalable DevOps pipelines to support AI-driven applications, including those leveraging ChatGPT and similar NLP models.
- Automate deployment, monitoring, and management of AI / ML models in production environments.
- Optimize infrastructure for AI workloads, ensuring efficient use of cloud or on-premises resources for training and inference tasks.
- Integrate ChatGPT and other AI services into applications, ensuring seamless functionality and performance.
- Collaborate with AI / ML engineers to streamline model development workflows and implement CI / CD processes for model updates.
- Monitor and maintain the health, performance, and security of AI-driven systems in production.
- Develop scripts and tools to automate repetitive tasks and improve operational efficiency.
- Stay updated on advancements in AI, DevOps tools, and practices, and recommend improvements to the tech stack.
Required Skills :
Strong expertise in DevOps practices, tools, and technologies (e.g., Docker, Kubernetes, Jenkins, Git, Terraform, etc.).Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud), including managing AI / ML workloads.Knowledge of AI / ML pipelines and familiarity with frameworks like TensorFlow, PyTorch, or Hugging Face.Proficiency in integrating and deploying APIs, including ChatGPT and other NLP models.Strong scripting skills (Python, Bash, etc.) for automation and tool development.Understanding of security best practices in AI applications and DevOps environments.Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment.Preferred Qualifications :
Experience with MLOps and tools like MLflow, Kubeflow, or SageMaker.Familiarity with large language models (LLMs) and their deployment nuances.Strong understanding of AI ethics, data privacy, and compliance requirements.Skills Required
Devops, Machine Learning, Artificial Intelligence, Ai