Remote Aws devops engineer kubernetes Jobs – 117 Open Jobs Today

AI/ML Engineer
Marga Darsana Consulting —Remote
- Up to ₹16,00,000 a year
- Full-time
- Remote
- Azure
- DevOps
- AWS
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5h
Sales Solutions Engineer - India
SonarSource —Remote
- Full-time
- Remote
- Azure
- DevOps
- English
- Work from home
Data & Backend Engineer
HelixBeat —Remote
- ₹15,00,000 - ₹24,00,000 a year
- Full-time
- Remote
- Azure
- DevOps
- Databases
- Work from home
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2h

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AI/ML Engineer

Marga Darsana Consulting
Remote

Quick apply

Job details

Full-time
Up to ₹16,00,000 a year
5 hours ago

Qualifications

CI/CD
Performance tuning
Cloud infrastructure
Azure
Kubernetes
Software deployment
DevOps
Microservices
AWS
Docker
Machine learning
Distributed systems
Terraform
Continuous integration
Scripting
APIs
ETL
S3
Kafka
Flask
AI
Python

Full job description

Urgent opening for Ai/ML Engineer

Job Title: AI/ML Engineer

Experience: 5-8 Years
Location: Gurgaon/Chennai(Remote)
Notice Period: Immediate to 15 days
Budget:11-14LPA

Mandatory Skills:AWS (SageMaker, S3, Glue, Kinesis, ECS, EKS), Python, Kubernetes & Docker, Kafka, FastAPI / Flask, Azure DevOps / AWS DevOps, Terraform / CloudFormation,ML deployment, automation & scalable data pipelines

Job Summary

We are looking for a skilled AI/ML Engineer with strong expertise in cloud engineering, DevOps practices, and machine learning operations. The ideal candidate will have hands-on experience in deploying, monitoring, and scaling ML models in production environments along with building robust data pipelines and automation frameworks.

This role requires a blend of ML engineering, cloud infrastructure, and DevOps capabilities to enable efficient and scalable AI solutions.

Key Responsibilities

Design, develop, and deploy scalable machine learning models in production environments
Build and maintain automated ML pipelines and workflows
Develop and manage data pipelines (ETL/ELT) for large-scale data processing
Implement CI/CD pipelines for ML and application deployment
Work with cross-functional teams to integrate ML solutions into business applications
Monitor model performance and ensure reliability, scalability, and accuracy
Develop APIs for ML services using frameworks like FastAPI or Flask
Implement event-driven architectures and streaming solutions
Automate infrastructure provisioning using Infrastructure as Code (IaC) tools
Optimize cloud resources and ensure cost-effective deployments

Required Skills

5+ years of experience in Cloud Engineering, DevOps, or ML Engineering
Strong hands-on experience with AWS services such as:
SageMaker
S3
Glue
Kinesis
ECS / EKS
Proficiency in Python for automation, scripting, and API development
Experience with Kubernetes and container orchestration
Strong understanding of ML model deployment and monitoring
Knowledge of event-driven architectures and streaming tools like Kafka
Experience with CI/CD pipelines using Azure DevOps or AWS DevOps tools
Hands-on experience in building data pipelines (ETL/ELT workflows)
Experience in developing APIs using FastAPI / Flask
Familiarity with Infrastructure as Code (Terraform, CloudFormation, etc.)

Preferred Qualifications

Experience working in multi-cloud environments
Exposure to MLOps frameworks and tools
Strong understanding of distributed systems and microservices architecture
Experience in performance tuning and optimization of ML systems

Pay: Up to ₹1,600,000.00 per year

Work Location: Remote

Quick apply

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