1. Design, implement, and manage the deployment of ML pipelines for video processing tasks, including real-time video stream analysis using NVIDIA 2.DeepStream, on Kubernetes clusters.
3. Automate the deployment of scalable and resilient ML workloads using Kubernetes and Karpenter to efficiently manage resources across AWS Spot and On-Demand instances.
4..Optimize infrastructure for cost and performance, ensuring high availability and fault tolerance of ML workloads.
5. Collaborate with data scientists and ML engineers to containerize and deploy ML models, ensuring seamless integration into our video analytics platform.
6. Implement robust monitoring, logging, and alerting mechanisms to ensure the health and performance of ML workloads.
7. Develop and maintain CI/CD pipelines for automated testing, building, and deployment of ML applications and infrastructure changes.
8. Stay abreast of the latest in cloud computing, containerization, and ML deployment strategies to continually improve our platform's efficiency and scalability.
Requirements:
1. Bachelor s or Master s degree in Computer Science, Engineering, or a related field
2. Proven experience in MLOps, DevOps, or similar roles with a focus on ML/AI workloads
3. Strong background in Kubernetes, including experience with automating cluster management and workload scaling using tools like Karpenter
4. Experience with cloud computing platforms, preferably AWS, and managing Spot/on-demand instances for cost optimization
5. Familiarity with ML lifecycle management tools and practices, including model deployment, monitoring, and versioning
6. Proficient in scripting and automation with languages such as Python, Bash, or similar
7. Experience with containerization technologies (Docker) and orchestration systems (Kubernetes)
8. Knowledge of infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation) is a plus
9. Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment
Skill(s) required
Amazon Web Services (AWS)American EnglishCI/CDCloud ComputingData AnalyticsDevOpsDockerEffective CommunicationKubernetesMachine LearningPythonStatistical Modeling
2.Opportunity to work on cutting-edge ML projects with a significant impact.
3.A dynamic and supportive team environment with opportunities for professional growth and development.
4.Remote work options and flexible working hours to support work-life balance.
Who can apply
1. Candidate must be available to work from 4:30 pm - 1:30 am Indian Standard Time (as the company is based outside of India & their local work timings are 6:00 am - 3:00 pm Eastern Standard Time)
Salary
Duration: 3 months
Salary during probation: ₹600,000 - 1,000,000 /month
