Senior Software Development Engineer (DevOps) - Video Insights

7018 Jiostar India Private Limited

Bengaluru

On-site

INR 1,800,000 - 2,600,000

Full time

14 days+
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Job summary

JioStar India Private Limited is seeking a Senior DevOps Engineer to design and maintain scalable cloud infrastructure powering AI/ML workloads and video systems. You will run Kubernetes clusters, GPU-accelerated deployment pipelines, and implement comprehensive monitoring and CI/CD practices.

You will collaborate with ML engineers to optimize MLOps pipelines, ensure security and data governance, and mentor teams on best practices in cloud architecture.

Qualifications

  • 4+ years of infrastructure, DevOps, or cloud platform engineering experience.
  • Hands-on expertise with Kubernetes and container orchestration (Docker, Kubernetes).
  • Experience with GPU infrastructure, CUDA, or accelerated computing environments.

Responsibilities

  • Design and implement robust, scalable cloud infrastructure for deploying video AI models and services.
  • Build and maintain Kubernetes clusters and containerized deployment pipelines optimized for GPU workloads.
  • Establish monitoring, logging, and observability systems for AI/ML production services.
  • Develop infrastructure-as-code practices and automation for rapid, reliable deployment.
  • Optimize cloud costs while maintaining performance and reliability standards.
  • Work with ML engineers to develop efficient MLOps pipelines for model training, evaluation, and serving.
  • Establish and maintain security, compliance, and data governance practices for AI systems.
  • Mentor engineering teams on infrastructure best practices and cloud architecture patterns.
  • Drive incident response, postmortems, and continuous improvement of system reliability.

Skills

Kubernetes
Docker
Python
Go
Distributed systems
CI/CD
Monitoring
GPU infrastructure
ML infra tools

Education

Bachelors/Masters in Computer Science or related

Tools

Terraform
CloudFormation
Helm
Kubeflow
MLflow

Job description

Job Summary

You are a systems-oriented engineer passionate about building reliable, scalable infrastructure for AI and ML workloads. You have deep expertise in cloud platforms, containerization, and distributed systems. You thrive on solving complex operational challenges and are motivated by enabling engineering teams to ship reliably and efficiently. You constantly seek to improve systems for reliability, observability, and developer experience. The pace of our growth is incredible – if you want to build world-class infrastructure for cutting-edge video AI systems at scale, join us!

About the team

Join our Video CoE as a Senior DevOps Engineer and build the infrastructure that powers next-generation video AI systems. You'll architect and maintain systems that enable ML engineers to rapidly iterate and deploy state-of-the-art video understanding models at massive scale. This role combines deep systems expertise with exposure to cutting-edge AI technology, offering the opportunity to shape how modern video AI infrastructure is built and deployed.

Key Responsibilities
  • Design and implement robust, scalable cloud infrastructure for deploying video AI models and services
  • Build and maintain Kubernetes clusters and containerized deployment pipelines optimized for GPU workloads
  • Establish monitoring, logging, and observability systems for AI/ML production services
  • Develop infrastructure-as-code practices and automation for rapid, reliable deployment
  • Optimize cloud costs while maintaining performance and reliability standards
  • Work with ML engineers to develop efficient MLOps pipelines for model training, evaluation, and serving
  • Establish and maintain security, compliance, and data governance practices for AI systems
  • Mentor engineering teams on infrastructure best practices and cloud architecture patterns
  • Drive incident response, postmortems, and continuous improvement of system reliability
Skills and attributes for success
  • 4+ years of infrastructure, DevOps, or cloud platform engineering experience
  • Deep hands-on expertise with Kubernetes and container orchestration (Docker, Kubernetes)
  • Expert proficiency in at least one major cloud platform (AWS, GCP, or Azure)
  • Strong programming background in Python, Go, or similar languages
  • Deep understanding of distributed systems, networking, and storage concepts
  • Experience with GPU infrastructure, CUDA, or other accelerated computing environments
  • Hands-on experience with ML infrastructure tools and frameworks (Kubeflow, MLflow, Ray, or similar)
  • Strong understanding of infrastructure-as-code tools (Terraform, CloudFormation, Helm)
  • Experience with CI/CD pipelines and automation frameworks
  • Passion for monitoring, logging, and observability – experience with Prometheus, ELK, Datadog, or similar
  • Experience with database and storage systems optimization for large-scale workloads
Preferred education and experience
  • Bachelors/Masters in Computer Science or a related field with 4-7 years of professional experience.

Perched firmly at the nucleus of spellbinding content and innovative technology, JioStar is a leading global media & entertainment company that is reimagining the way audiences consume entertainment and sports.

Its television network and streaming service together reach more than 750 million viewers every week, igniting the dreams and aspirations of hundreds of million people across geographies.

JioStar India Private Limited (formerly known as Star India Private Limited) is an equal opportunity employer.

The company values diversity and its mission is to create a workplace where everyone can bring their authentic selves to work.

The company ensures that the work environment is free from any discrimination against persons with disabilities, gender, gender identity and any other characteristics or status that is legally protected.

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