MLOps Engineer

Job Summary

The MLOps Engineer plays a critical role in designing, deploying, and managing machine learning (ML) infrastructure and workflows within the organization. This position aims to optimize the ML lifecycle and ensure the smooth operation of workloads, contributing significantly to the organization’s goals of leveraging machine learning technologies.

Responsibilities

• Design and scale ML infrastructure across clusters to support model training and deployment.
• Deploy and manage ML workflows using Kubernetes, Helm, ArgoCD, and ArgoWorkflows ensuring robustness and efficiency.
• Implement and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for the entire ML lifecycle.
• Monitor, optimize, and secure workloads utilizing tools such as Prometheus, Grafana, and AWS Logging Tools.

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Technical Skills:
  • Expertise in Python and Go programming.
  • Proficiency in machine learning frameworks like TensorFlow and PyTorch.
  • Hands-on experience with Docker, Kubernetes, and GPU acceleration.
  • Familiarity with AWS services including EKS, EC2, VPC, IAM, S3, and EFS.
  • Deep understanding of distributed computing and orchestration.

Preferred Skills

• Additional experience with other cloud platforms and tools is a plus.
• Knowledge of more advanced orchestration methods and tools will be beneficial.

Experience

• Minimum of 3 years of relevant experience in MLOps or related fields.

Environment

• Work will be based in Chennai, with specifics of remote or in-office arrangements not provided.

Salary

(Salary information not provided)

Growth Opportunities

(Opportunities for career advancement not provided)

Benefits

(Details on benefits not provided)