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Machine Learning +Aws+ (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) +Sagemaker

Machine Learning +Aws+ (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) +Sagemaker

DigiHelic Solutions Pvt. Ltd.Rajkot, IN
1 day ago
Job description

Job Role : ML Engineer

Experience : 6-12 Years

Location : Pune, Bangalore, Hyderabad, Trivandrum, Chennai, Kochi, Gurgaon, Noida

Key Summary :

  • The MLE will design, build, test, and deploy scalable machine learning systems,

optimizing model accuracy and efficiency

  • Model Development : Algorithms and architectures span traditional statistical methods to

    • deep learning along with employing LLMs in modern frameworks.

  • Data Preparation : Prepare, cleanse, and transform data for model training and

    • evaluation.

  • Algorithm Implementation : Implement and optimize machine learning algorithms and

    • statistical models.

  • System Integration : Integrate models into existing systems and workflows.
  • Model Deployment : Deploy models to production environments and monitor

    • performance.

  • Collaboration : Work closely with data scientists, software engineers, and other

    • stakeholders.

  • Continuous Improvement : Identify areas for improvement in model performance and

    • systems.

    Skills :

  • Programming and Software Engineering : Knowledge of software engineering best

    • practices (version control, testing, CI / CD).

  • Data Engineering : Ability to handle data pipelines, data cleaning, and feature

    • engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for

    troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch,

    Neo4J graph

  • Model Deployment and Monitoring : MLOps Experience in deploying ML models to

    • production environments.

  • Knowledge of model monitoring and performance evaluation.

    • Required experience :

  • Amazon SageMaker : Deep understanding of SageMaker's capabilities for building,

    • training, and deploying ML models; understanding of the Sagemaker pipeline with ability

    to analyze gaps and recommend / implement improvements

  • AWS Cloud Infrastructure : Familiarity with S3, EC2, Lambda and using these services in

    • ML workflows

  • AWS data : Redshift, Glue
  • Containerization and Orchestration : Understanding of Docker and Kubernetes, and their

    • implementation within AWS (EKS, ECS)

    Skills :

    Aws, Aws Cloud, Amazon Redshift, Eks

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    Machine Learning • Rajkot, IN