We are seeking a Senior AI-Ops Engineer with 4 to 8 years of experience to join our Generative AI team. The ideal candidate will have extensive experience in MLOps practices, cloud infrastructure, automation tools, and a deep understanding of AI technologies. In this role, you will set up and manage IT infrastructure, develop automation scripts, and implement CI/CD pipelines to support the development and deployment of generative AI models.
Key Responsibilities:
- Infrastructure Management: Set up and manage the necessary IT infrastructure, including cloud services, servers, and storage, to support the development and deployment of generative AI models.
- Automation Development: Develop and deploy automation tools and scripts to streamline repetitive tasks, such as system updates, backups, and scaling of resources.
- CI/CD Implementation: Implement continuous integration and continuous deployment (CI/CD) pipelines to automate the deployment and update processes for generative AI models.
- Security Implementation: Implement and maintain security measures to protect data and AI models from unauthorized access, breaches, and other threats.
- Monitoring Solutions: Implement monitoring solutions to continuously track the performance, availability, and health of IT systems and AI models.
Must-Have Skills:
- Prompt Engineering: Expertise in crafting and optimizing prompts for AI models.
- LLM Interactions: Experience working with large language models (LLMs).
- OpenAI: Familiarity with OpenAI's tools and platforms.
- Deployment for Gen AI: Experience in deploying generative AI models.
- Docker and Kubernetes: Proficiency in containerization and orchestration using Docker and Kubernetes.
- GIT: Strong knowledge of GIT for source control.
- CI/CD: Experience with CI/CD pipeline
- Model Monitoring: Skills in monitoring the performance of deployed AI models.
- Deployment: Experience in deploying AI models and IT infrastructure
- Traditional ML: Knowledge of traditional machine learning algorithms such as regression, classification, and clustering.
- Certifications: Microsoft Azure Certifications at Associate/ Expert/ Specialty Level will be good to have. However, AZ-400 Certified candidate will be preferred for this role.
Good-to-Have Skills:
- Workflow Orchestration: Experience with workflow orchestration tools such as Azure Data Factory or Airflow.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- 4-8 years of experience in MLOps, DevOps, or a related role.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
- Eagerness to learn and adapt to new technologies and methodologies.
Job Type: Full-time
Benefits:
- 401(k)
- Dental insurance
- Flexible schedule
- Health insurance
- Paid time off
- Referral program
- Relocation assistance
- Vision insurance
Schedule:
- Day shift
- Monday to Friday
Experience:
- Generative AI: 1 year (Required)
- AI models: 1 year (Required)
- AIOps: 1 year (Required)
- Azure: 2 years (Required)
- AI chatbots: 1 year (Required)
- CI/CD: 1 year (Required)
Work Location: Remote