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.
