What you’ll do:

• Platform Maintenance:

• Monitor the health and performance of our GCP-based machine learning infrastructure, including compute instances, storage, and networking.

• Troubleshoot and resolve issues related to resource allocation, deployment, and configuration of ML models and pipelines.

• Collaborate with DevOps teams to implement automated deployment and testing processes for machine learning solutions.

• Incident Management:

• Triage and resolve support requests related to our ML platform infrastructure.

• Perform root cause analysis to identify and prevent future problems.

• Develop and maintain documentation on incident resolution procedures.

• Performance Optimization:

• Investigate and address performance bottlenecks in our ML environment on GCP.

• Implement monitoring and alerting systems to proactively identify potential issues.

• Collaborate with data science teams to optimize resource utilization and cost efficiency.

• Platform Upgrades and Enhancements:

• Stay up-to-date on new GCP services and releases relevant to machine learning.

• Plan and execute platform upgrades and enhancements to support evolving ML needs.

• Work with data science and engineering teams to assess the impact of new technologies and services on existing workflows.

What experience you need:

• BS degree in Computer Science or related technical field involving coding with 

• 7+ years of experience in Cloud Platform Engineer with good knowledge on VI Platform Engineering

• Strong knowledge of GCP services, particularly those related to machine learning (e.g., Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery).

• Proficiency in Python and experience with scripting languages.

• Experience with containerization (e.g., Docker) and orchestration technologies (e.g., Kubernetes).

• Familiarity with cloud monitoring and logging tools (e.g., Cloud Monitoring, Cloud Logging).

• Experience with DevOps practices and tools (e.g., CI/CD pipelines, Git).

• Ability to quickly diagnose and resolve complex technical issues.

• Strong analytical and troubleshooting skills.

• Proactive approach to identifying and preventing potential problems.

• Ability to effectively communicate technical concepts to both technical and non-technical stakeholders.

• Excellent written and verbal communication skills.

• Ability to collaborate effectively with cross-functional teams.