Lead MLOps Architect
hace 6 días
We are looking for a Senior Cloud Infrastructure Engineer with a strong background in MLOps to architect, implement, and sustain optimal infrastructure and deployment methodologies for Machine Learning pipelines and models. Your expertise in AI infrastructure, automation, and cloud services will be crucial for our operations.
Key Responsibilities
- Architect, develop, and uphold scalable and resilient infrastructure for AI/ML systems, focusing on cloud environments, containerization, and orchestration technologies.
- Create and execute CI/CD pipelines to streamline the deployment, testing, and monitoring of AI/ML models and applications.
- Assess and incorporate new tools, technologies, and frameworks to enhance the efficiency and effectiveness of our MLOps workflows.
- Design and oversee Continuous Deployment processes utilizing Kubernetes, ArgoCD, and Jenkins.
- Manage associated container and model registries.
- Track infrastructure usage and expenses related to model training, inference, and GPU performance.
- Oversee and resolve issues within AI/ML systems to guarantee high availability, performance, and reliability.
Qualifications
- Minimum of 4 years of experience in a DevOps Engineer role.
- At least 1 year of experience managing AI/ML infrastructure in cloud environments.
- Extensive hands-on experience with at least one public cloud platform, preferably AWS.
- Proficiency in Python or another programming language.
- Experience with Docker and Kubernetes in a production setting.
- Familiarity with Continuous Deployment tools such as Jenkins or ArgoCD.
- Experience with Logging and Monitoring tools for SaaS applications like Sumo, Splunk, Datadog, etc.
- Strong command of the English language.
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