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    MLOps Platform Engineer - Gurugram, India - Cars24

    Cars24
    Cars24 Gurugram, India

    2 hours ago

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    Description

    About the Role :

    This role is for you if you are passionate about machine learning, data engineering and building products in general.

    It will require close collaboration with data scientists, analysts and software engineers, so a basic understanding of DS stack and development in Python will be useful.

    Following is a representative list of what you will be doing but not limited to what is mentioned.

    Required Experience : 3-5 years

    What You Will Do :


    • Collaborate with data scientists to optimise ML models for highthroughput, lowlatency use cases
    • Setup infrastructure for Deep Learning/GPT usecases which require scaled up training with cost optimization
    • Engineer highreliability, highperformance services for sophisticated MLdriven functionality
    • Suggest and design deployment methods on cloud infrastructure (kubernetes, cloud function etc)
    • Design and build our reporting, data/model version control and model deployment stack to help data scientists productionize their models and features faster
    • Build and maintain DS/BI warehouse that serves internal tools and interfaces to improve the productivity of the team and improve the accessibility of our products
    • You would serve as the bridge between the data scientists and software engineers
    • Enable efficient monitoring, maintenance and debugging of production ML models
    • Work with data scientists to make production code more robust in terms of scalability, latency and compute.
    Key skills required :


    • Understanding of code optimization and writing high performance methods
    • Self learning attitude, we work with latest/opensource technologies and need people who can take full ownership of any new implementation with minimal supervision
    • Knowledge of version control, proficiency in Python, deployment related best practices and enthusiasm towards MLOps
    • Experience with web services and microservice architectures
    • Cloud Service Provider (GCP/AWS), Kubernetes
    • Scaling ML models in highthroughput and lowlatency settings
    • Ability to think through LLD and HLD
    Good to have/Willing to learn :

    • Data science knowledge and familiarity with ML libraries such as Pandas, Scikit, Tensorflow, XGBoost, Keras etc., will help in taking models to production and serving
    • SQL/Big Data, MLOps knowledge
    )
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