Senior MLOps Engineer

2 months ago

Bengaluru, India Avataar Full time
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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