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CoreOps.AI - DevOps Engineer - MLOps

CoreOps.AI - DevOps Engineer - MLOps

COREOPS.AI PRIVATE LIMITEDNoida
11 days ago
Job description

Job Description :

Role : DevOps / ML-Ops Engineer :

We are seeking a highly skilled DevOps Engineer with strong MLOps expertise to join our team. The ideal candidate will have a solid foundation in DevOps practices - infrastructure automation, CI / CD, container orchestration, networking, monitoring, Linux system administration, and security compliance - and extend this expertise into operationalizing ML / AI workloads. You will collaborate with data scientists, ML engineers, and software teams to ensure reliable, secure, and scalable deployments of applications and ML models.

Key Responsibilities :

DevOps :

  • Design, build, and maintain CI / CD pipelines for applications and AI / ML workloads.
  • Implement Infrastructure as Code (Terraform, Ansible, CloudFormation).
  • Deploy and manage containerized environments using Docker, Kubernetes, and Helm.
  • Manage and optimize cloud infrastructure across AWS, Azure, or GCP.
  • Ensure system reliability, security, and performance with strong Linux administration skills.
  • Manage web servers, DNS, CDN, and databases (SQL / NoSQL).
  • Implement monitoring, logging, and alerting using Prometheus, Grafana, ELK, or Datadog.
  • Apply best practices for networking (VPCs, load balancers, DNS, firewalls, service meshes), scaling, and cost optimization.

MLOps :

  • Deploy, monitor, and maintain ML models in production.
  • Build automated training, testing, retraining, and data drift detection pipelines.
  • Support data pipelines, versioning, and reproducibility (DVC, MLflow, CML).
  • Collaborate with data scientists and ML engineers to productionize ML models.
  • Integrate ML / AI workflows into CI / CD processes.
  • Work with APIs (REST / gRPC) for model / service integration.
  • Security & Compliance :

  • Design secure, compliant systems (IAM, RBAC, secrets management, audit readiness).
  • Implement DevSecOps practices in CI / CD pipelines.
  • Ensure alignment with industry standards (GDPR, SOC2, ISO27001).
  • Must-Have Skills :

  • Linux expertise : Strong hands-on Linux administration (Ubuntu, RHEL, CentOS).
  • DevOps foundation : CI / CD, Kubernetes, Docker, Terraform / Ansible, monitoring, and security.
  • Cloud experience : Hands-on with AWS, Azure, or GCP.
  • Networking expertise : Strong knowledge of VPCs, load balancers, DNS, firewalls, and service meshes.
  • Web infrastructure : Experience with Nginx, Apache, DNS management, CDN integration.
  • Database experience : SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Redis).
  • Programming : Proficiency in Python, Bash / Shell scripting, and SQL.
  • MLOps knowledge : Model deployment, pipelines, monitoring, retraining, and data drift detection.
  • Version control & automation : GitHub / GitLab, Jenkins, GitHub Actions.
  • ML frameworks : Familiarity with TensorFlow, PyTorch, or Scikit-learn.
  • RAG & AI pipeline exposure : RAG pipelines, vector databases (Pinecone, Weaviate, FAISS), Collaboration tools : Jira, Azure DevOps, Confluence.
  • Preferred Skills :

  • Observability and monitoring for ML / AI systems.
  • Familiarity with cloud-native ML platforms (SageMaker, Vertex AI, Azure ML).
  • Experience with workflow / data orchestration (Airflow, Argo, Kubeflow).
  • Security practices in DevOps / MLOps (secrets management, IAM, RBAC, compliance).
  • Knowledge of LLMOps best practices (monitoring, evaluation, guardrails).
  • Certifications (optional but attractive) :
  • AWS / Azure / GCP Certified Solutions Architect or DevOps Engineer.
  • Kubernetes Bachelors or Masters degree in Computer Science, Engineering, or related field.
  • 4+ years of experience in DevOps (cloud, containers, automation, Linux, networking) and 2+ years of MLOps exposure in production environments.
  • Strong understanding of DevOps and MLOps principles and best practices.
  • (ref : hirist.tech)

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