DevOps Engineer

3 weeks ago

Mangalore, Karnataka, India Omneky Full time
Job Description:

DevOps Engineer

Location:

India (Remote)
Compensation:

₹25 lakh - ₹45 lakh (based on skills and experience)
Working Hours:

Syncing with USA team in PST time zone

About Us:
At Omneky, we are redefining digital advertising through AI-powered personalized content at scale. Our mission is to revolutionize advertising performance by leveraging AI models to deliver optimal results across global markets and channels. We are looking for an experienced DevOps Engineer with exposure to ML Ops to join our India-based team and collaborate with our USA team in building world-class infrastructure for scalable AI/ML solutions.

Role Overview:
As a DevOps Engineer, you will design, implement, and optimize cloud-based infrastructure and CI/CD pipelines to support both traditional software applications and AI/ML workflows. You will focus on infrastructure automation, security, monitoring, and scalability, with some focus on enabling efficient machine learning model deployment in production.

Key Responsibilities:
ML Infrastructure Management:

Design, deploy, and manage machine learning models using AWS services like ECS, EC2, EKS, and Sagemaker.
Networking & Security:

Set up secure VPCs and implement robust networking practices to ensure secure and compliant communication across AWS components.
Deployment:

Automate and streamline the deployment processes of ML models and AI applications using tools such as Docker, Kubernetes, and Sagemaker.
Infrastructure as Code (IaC):

Develop and maintain infrastructure using tools like Terraform, CloudFormation, or similar IaC tools to achieve scalable, repeatable, and efficient deployment.
Monitoring & Compliance:

Implement monitoring solutions for models and infrastructure (using tools like CloudWatch, Prometheus, Grafana, etc.) to maintain uptime and compliance with SOC2 security standards.
Data Management:

Collaborate with data scientists and data engineers to optimize data storage and retrieval processes using S3 and other AWS storage solutions.
Performance Optimization:

Work closely with ML engineers and data scientists to optimize the performance and scalability of deployed models in a production environment.
CI/CD Pipelines:

Develop CI/CD pipelines to automate the testing, deployment, and scaling of AI applications and models.
Troubleshooting & Maintenance:

Diagnose, troubleshoot, and resolve issues related to infrastructure, models, and applications in production.
Documentation & Training:

Document infrastructure designs, processes, and best practices, and provide guidance to team members on deploying models effectively.

Requirements:

Experience:

4+ years of experience as a

DevOps Engineer

,

Cloud Engineer

, or in a related role. Experience with

ML Ops

workflows is a plus.
Cloud Expertise:

Strong hands-on experience with

AWS services

(ECS, EC2, EKS, VPC, IAM, S3).
IaC Proficiency:

Proven expertise with

infrastructure-as-code (IaC)

tools such as

Terraform

,

CloudFormation

, or

Ansible

.
CI/CD:

Strong knowledge of building

CI/CD pipelines

using tools such as

Jenkins

,

GitHub Actions

,

GitLab CI

, or

AWS CodePipeline

.
Containerization:

Hands-on experience with

Docker

and

Kubernetes

for container orchestration.
Monitoring Tools:

Familiarity with monitoring and logging tools such as

CloudWatch

,

Prometheus

,

Grafana

, and

Datadog

.
Security:

Experience with setting up

secure cloud environments

, including

IAM roles, VPCs

, and

SOC2 compliance

processes.
Collaboration:

Excellent communication and collaboration skills to work with global teams, especially across different time zones.
Education:

Bachelor's or Master's degree in

Computer Science, Engineering

, or a related field.

What We Offer:

Competitive salary package ranging from ₹25 lakh to ₹45 lakh, depending on skills and experience.
Flexible working hours to sync with the USA (PST) team.
Opportunities to work on cutting-edge AI and cloud projects with a global impact.
A collaborative, inclusive, and growth-oriented work environment.
Learning and development programs to support continuous professional growth.

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