DevOps Engineer

1 week ago

Pune, Maharashtra, India Onelab Ventures Full time ₹ 20,00,000 - ₹ 25,00,000 per year

About the Role

We are looking for a skilled
DevOps Engineer with strong MLOps expertise
to join our team. The ideal candidate will have hands-on experience in
AWS Cloud, scripting, and automation
, along with proven skills in
deploying and managing machine learning pipelines in production
.

Key Responsibilities

  • Design, implement, and maintain
    CI/CD pipelines
    for ML model training, testing, and deployment.
  • Manage
    containerization & orchestration
    using Docker and Kubernetes.
  • Automate infrastructure provisioning using
    Terraform/CloudFormation
    .
  • Implement and manage
    MLOps tools
    (Kubeflow, MLflow, Airflow, SageMaker, etc.).
  • Ensure
    scalability, reliability, and monitoring
    of ML/AI production systems.
  • Work closely with
    data scientists and ML engineers
    to operationalize ML models.
  • Develop
    automation scripts
    in Python/Bash to streamline workflows.
  • Implement and manage
    AWS cloud services
    (EC2, S3, EKS/ECS, Lambda, RDS, IAM, Secrets Manager).
  • Ensure compliance with
    security, cost optimization, and performance best practices
    .

Required Skills & Experience

  • 7+ years
    of experience as a DevOps/MLOps Engineer.
  • Strong hands-on expertise in
    AWS Cloud
    (compute, storage, serverless, IAM).
  • Solid knowledge of
    CI/CD tools
    (GitLab CI/CD, Jenkins, ArgoCD).
  • Proficiency in
    Docker & Kubernetes
    for container orchestration.
  • Experience with
    MLOps tools
    : Kubeflow, MLflow, Airflow, SageMaker, or similar.
  • Strong scripting/programming skills in
    Python and Bash
    .
  • Experience with
    monitoring/logging tools
    (Prometheus, Grafana, ELK stack).
  • Familiarity with
    data version control
    (DVC, Git) and
    feature stores
    is a plus.
  • Excellent troubleshooting and problem-solving skills.

Good to Have

  • Experience with
    multi-cloud (GCP/Azure ML)
    .
  • Familiarity with
    TorchServe, BentoML, KFServing
    for model serving.
  • Knowledge of
    security & compliance in ML pipelines
    .

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