Work From Home India Devops engineer Jobs – 71 Open Jobs Today

MLOps Engineer / AI Ops Engineer
Botmet Technologies Private Limited —Remote
- From ₹8,00,000 a year
- Full-time
- Remote
- Azure
- Master's degree
- Machine learning
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- Full-time
- Remote
- Azure
- Computer Science
- Software troubleshooting
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- Full-time
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- Azure
- Computer Science
- DevOps
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MLOps Engineer / AI Ops Engineer

Botmet Technologies Private Limited
Remote

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Job details

Full-time | Contractual / Temporary
From ₹8,00,000 a year
3 days ago

Qualifications

CI/CD
Azure
Law
Kubernetes
Git
Master's degree
Docker
Machine learning
Continuous integration
REST
GitHub
APIs
AI
Jenkins
Communication skills
Python
High availability

Full job description

Experience- 5+ Years

We are looking for an experienced MLOps / AI Ops Engineer to design, build, and manage enterprise AI/ML platforms. The ideal candidate should have hands-on experience in MLOps, AI Platform Engineering, Feature Stores, Model Registry/Catalog, AI Governance, Kubernetes, Azure, and production AI deployments.

Key Responsibilities

Design and maintain enterprise AI/ML platforms.
Build and manage Feature Stores and Model Registry/Catalog.
Develop scalable MLOps pipelines for model training, deployment, and monitoring.
Implement AI Governance, security, compliance, and observability.
Deploy AI/ML workloads using Kubernetes and Docker.
Build and manage Agentic AI platform infrastructure and AI Agent Catalog.
Collaborate with Data Scientists, Software Engineers, and DevOps teams.
Monitor production AI systems and ensure high availability.

Required Skills

5+ years of experience in MLOps, AI Platform Engineering, or AI Ops.
Strong experience with Feature Stores (Feast, Databricks Feature Store, Azure ML Feature Store).
Experience with Model Registry/Catalog (MLflow, Azure ML Registry, SageMaker Model Registry).
Hands-on experience with MLOps tools (Kubeflow, MLflow, Airflow, GitHub Actions, Jenkins).
Experience with Kubernetes, Docker, Python, and REST APIs.
Knowledge of Azure Cloud (preferred).
Experience with AI Governance, model monitoring, security, and observability.
Exposure to LLM platforms and Agentic AI is an added advantage.
Excellent communication and problem-solving skills.

Preferred Qualifications

Experience designing enterprise AI platforms.
Experience supporting production AI/ML workloads.
Knowledge of CI/CD for machine learning pipelines.

Pay: From ₹800,000.00 per year

Application Question(s):

How many years of hands-on experience do you have in MLOps or AI Platform Engineering?
Have you worked on enterprise AI/ML platform architecture?
Have you implemented or managed a Feature Store in a production environment?
Which Feature Store(s) have you worked with?
Have you worked with Model Registry or Model Catalog solutions (e.g., MLflow, Azure ML Registry, SageMaker Model Registry)?
Which cloud platform have you primarily worked on?
If selected, how soon can you join (Days)?
Notice Period, CCTC and ECTC?

Work Location: Remote

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