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    Machine Learning Engineer - Bangalore, India - Internshala

    Internshala
    Internshala Bangalore, India

    5 days ago

    Default job background
    permanent Technology / Internet
    Description

    About the job:
    Internshala is assisting Livesitter in hiring for MLOps Engineer - Video Analytics Platform (Remote)

    Livesitter -We leverage cutting-edge AI to provide a seamless and secure childcare experience for both parents and Design, implement, and manage the deployment of ML pipelines for video processing tasks, including real-time video stream analysis using NVIDIA


    • DeepStream, on Kubernetes clusters.
    • Automate the deployment of scalable and resilient ML workloads using Kubernetes and Karpenter to efficiently manage resources across AWS Spot and On-Demand instances.
    • Optimize infrastructure for cost and performance, ensuring high availability and fault tolerance of ML workloads.
    • Collaborate with data scientists and ML engineers to containerize and deploy ML models, ensuring seamless integration into our video analytics platform.
    • Implement robust monitoring, logging, and alerting mechanisms to ensure the health and performance of ML workloads.
    • Develop and maintain CI/CD pipelines for automated testing, building, and deployment of ML applications and infrastructure changes.
    • Stay abreast of the latest in cloud computing, containerization, and ML deployment strategies to continually improve our platform's efficiency and Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
    • Proven experience in MLOps, DevOps, or similar roles with a focus on ML/AI workloads.
    • Strong background in Kubernetes, including experience with automating cluster management and workload scaling using tools like Karpenter.
    • Experience with cloud computing platforms, preferably AWS, and managing Spot/On-Demand instances for cost optimization.
    • Familiarity with ML lifecycle management tools and practices, including model deployment, monitoring, and versioning.
    • Proficient in scripting and automation with languages such as Python, Bash, or similar.
    • Experience with containerization technologies (Docker) and orchestration systems (Kubernetes).
    • Knowledge of infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation) is a plus.
    • Strong problemsolving skills and the ability to work in a fastpaced, dynamic environment.
    )
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