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    Senior MLOps Engineer - Bengaluru, India - Avataar

    Avataar
    Avataar Bengaluru, India

    2 days ago

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    Description

    At Avataar, we are re-imagining product discovery for shopping/commerce with the power of spatial depth. We are taking the latest advances in Neural Rendering, Computer Graphics, Generative models and the web to empower the next generation of visual storytelling.

    We recently announced our $45mm Series-B from top-tier global investors including Tiger Global and Sequoia Capital.

    The position will be based out of our Bangalore office - Vaishnavi Tech Park, Bellandur, Bangalore

    Position: MLOps Engineer

    Position Overview:

    As the MLOps Engineer, you will be designing, developing and maintaining the infrastructure and workflows necessary to support the deployment and scaling of multiple concurrent machine learning services. The ideal candidate for this role has expertise in MLOps, automation, optimization, and cloud infrastructure which will be essential in scaling our machine learning capabilities and ensuring the reliable and efficient deployment of our computer vision models.

    Responsibilities:

    • Work on the development and implementation of MLOps processes, and best practices for the entire machine learning lifecycle, from model training to deployment and monitoring.
    • Design, build, and maintain robust, scalable, and secure ML infrastructure in the cloud (AWS), ensuring high availability and performance.
    • Develop infrastructure for large-scale distributed training and experimentation.
    • Collaborate closely with the backend team to integrate MLOps processes into the overall CI/CD pipeline and infrastructure.

    Qualifications & Experiences:

    • 3+ years of experience working in MLOps with hands-on experience in deploying and maintaining machine learning models in large-scale production environments.
    • Extensive experience with cloud platforms (AWS) and their machine learning services, including model deployment and monitoring.
    • Deep understanding of containerization technologies (e.g., Docker, Kubernetes) and experience with container orchestration.
    • Solid understanding of DevOps principles and experience with CI/CD pipelines, automated testing, and infrastructure-as-code
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