Senior DevOps Engineer - AI Services

at  ANACONDA INC

SUMMARY:

Anaconda is seeking a talented Senior Devops Engineer to join our rapidly growing company. This is an excellent opportunity for you to leverage your experience and skills and apply it to the world of data science, artificial intelligence, and machine learning.

What You’ll Do:

• Design and implement scalable AWS infrastructure, with particular focus on Lambda functions, RDS, and message bus architectures
• Build and maintain robust MLOps pipelines for deploying and monitoring LLM models in production environments
• Develop and optimize real-time communication systems using WebSockets and WebRTC for ML inference services
• Create and maintain Python packages with C extensions, focusing on performance optimization and reliability
• Design and implement comprehensive monitoring and telemetry systems across our infrastructure
• Manage and optimize Kubernetes clusters for ML workloads, ensuring efficient resource utilization and high availability
• Architect and maintain efficient CI/CD pipelines for both infrastructure and application deployments
• Collaborate with AI and research teams to understand and implement infrastructure requirements for new ML models and features
• Optimize system performance and cost efficiency across our AWS infrastructure
• Lead technical discussions and provide expertise in infrastructure and deployment strategies
• Implement and maintain security best practices across our infrastructure
• Participate in on-call rotations and lead incident response efforts when necessary

• Design and implement scalable AWS infrastructure, with particular focus on Lambda functions, RDS, and message bus architectures
• Build and maintain robust MLOps pipelines for deploying and monitoring LLM models in production environments
• Develop and optimize real-time communication systems using WebSockets and WebRTC for ML inference services
• Create and maintain Python packages with C extensions, focusing on performance optimization and reliability
• Design and implement comprehensive monitoring and telemetry systems across our infrastructure
• Manage and optimize Kubernetes clusters for ML workloads, ensuring efficient resource utilization and high availability
• Architect and maintain efficient CI/CD pipelines for both infrastructure and application deployments
• Collaborate with AI and research teams to understand and implement infrastructure requirements for new ML models and features
• Optimize system performance and cost efficiency across our AWS infrastructure
• Lead technical discussions and provide expertise in infrastructure and deployment strategies
• Implement and maintain security best practices across our infrastructure
• Participate in on-call rotations and lead incident response efforts when necessar