8 days ago
ML DevOps Engineer
Virtusa
On Site
Full Time
$160,000
Andhra Pradesh, India
Job Overview
Job TitleML DevOps Engineer
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$160,000
LocationAndhra Pradesh, India
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Job Description
Job Summary: ML DevOps Engineer at Virtusa
As an ML DevOps Engineer at Virtusa, you will be crucial in managing the infrastructure and pipelines necessary for scalable AI agent operations. This role demands a strong background in DevOps principles combined with expertise in machine learning operations to ensure efficient, secure, and robust deployment of AI agents.
Key Responsibilities
- Automate CI/CD pipelines to streamline the entire lifecycle of AI agents, ensuring rapid and reliable deployments.
- Manage and provision infrastructure using modern tools like Terraform, GKE (Google Kubernetes Engine), and Cloud Build.
- Implement comprehensive MLOps practices leveraging platforms such as Vertex AI Pipelines and MLFlow.
- Monitor the performance of AI agents and infrastructure, deploying advanced observability tools for proactive issue detection.
- Ensure secure Application-to-Application (A2A) communication and implement robust service mesh solutions.
- Collaborate closely with teams to establish and enforce best practices for data privacy and regulatory compliance.
Required Experience and Skills
- Over 5 years of experience in DevOps/MLOps engineering roles.
- Expert-level proficiency with Google Cloud Platform (GCP) services, including Vertex AI, GKE, BigQuery, and Pub/Sub.
- Extensive experience with containerization technologies such as Docker and orchestration platforms like Kubernetes.
- Familiarity with ML orchestration and pipeline tools like Kubeflow and Airflow.
- Proficiency with observability tools including Prometheus, Grafana, and Stackdriver.
- Strong understanding of machine learning model versioning and drift detection.
Key skills/competency
- MLOps
- DevOps
- CI/CD
- GCP
- Kubernetes
- Terraform
- Vertex AI
- MLFlow
- Observability
- AI Agents
How to Get Hired at Virtusa
- Research Virtusa's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume for MLOps: Customize your resume to highlight your GCP, Kubernetes, and CI/CD expertise, specifically for the ML DevOps Engineer role.
- Showcase MLOps projects: Prepare to discuss past projects demonstrating your ability to automate ML pipelines, manage infrastructure, and implement observability at Virtusa.
- Master GCP and MLOps tools: Deepen your knowledge of Vertex AI, Terraform, Docker, and Kubernetes, as these are critical technologies at Virtusa.
- Prepare for behavioral questions: Practice answering questions that demonstrate collaboration, problem-solving, and your commitment to best practices in secure and compliant ML operations.
Frequently Asked Questions
Find answers to common questions about this job opportunity
01What is the primary focus of the ML DevOps Engineer role at Virtusa?
02Which specific GCP services are essential for an ML DevOps Engineer at Virtusa?
03How important is MLOps experience for this Virtusa role?
04What kind of infrastructure management tools should I be familiar with for Virtusa's ML DevOps Engineer position?
05What interview insights can help me succeed for an ML DevOps Engineer role at Virtusa?
06What are the expectations regarding observability in this ML DevOps Engineer role at Virtusa?
07Is knowledge of model versioning and drift important for the ML DevOps Engineer at Virtusa?
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