Senior Cloud Engineer

Job summary

The Senior Cloud Engineer, ML Platforms is tasked with building and maintaining AWS-based cloud infrastructure to support machine learning activities in Computational Biology. Responsibilities include designing infrastructure for machine learning workloads, managing environments through Infrastructure as Code, and integrating technologies like Databricks and MLflow to enhance MLOps processes.

Qualifications

• Hands-on experience designing, implementing and supporting cloud infrastructure in AWS environments
• Strong knowledge of AWS services including SageMaker, IAM, networking, storage, compute services and container technologies
• Experience with Infrastructure as Code and cloud automation practices
• Understanding of cloud security, governance, compliance and access management principles
• Experience supporting machine learning, data science or MLOps platforms
• Knowledge of CI/CD practices and tools used for software and machine learning delivery
• Experience working with technologies such as Databricks, MLflow, Jenkins, Bitbucket, OpenShift or comparable platforms
• Ability to troubleshoot complex technical issues and continuously improve platform reliability, performance and efficiency

Responsibilities

• Design, maintain and continuously improve AWS-based infrastructure supporting machine learning workloads
• Manage cloud environments through Infrastructure as Code
• Monitor platform performance, availability, security findings and resource utilization
• Plan and manage cloud capacity, including CPU, GPU, storage and networking resources
• Build and support infrastructure for MLOps processes
• Develop reusable automation and platform capabilities
• Enable and maintain integrations between AWS services and supporting technologies
• Act as the primary technical contact for stakeholders
• Create and maintain technical documentation

Skills

Degrees

Relocation