Senior MLOps Engineer

1 month ago


Pune, Maharashtra, India Siemens Energy Full time

About the Role

We are seeking a highly skilled Senior MLOps Engineer to join our Digital Core function and play a key role in shaping the data architecture and strategy within the organization.

As a Senior MLOps Engineer, you will focus on developments around our Machine Learning environment, partnering with business stakeholders and other teams within the organization to define priorities for backlog items and work on those.

You will consult with stakeholders on AI ML to build best-in-class solutions, support test automation, build CI CD pipelines, and work on PoCs/MVPs using different hyperscale offerings.

Passionate about the environment and climate change? Ready to be part of the future of the energy transition? Our team is looking for innovative, enthusiastic, and versatile data, digital, and AI professionals to drive us forward on this exciting venture.

Key Responsibilities

  • Onboard new AI ML use cases in AWS / Google Cloud Platform.
  • Define the right MLOps architecture for AWS/ GCP/ Cloud Agnostic.
  • Experience in Cross Account Model Deployment, monitoring, sharing.
  • Very strong experience in working with AI ML services (AWS Sagemaker, GCP AutoML, Vertex AI etc.).
  • Develop PoC's / MVP's using AWS / GCP and other MLOps services.
  • Hands-on experience in GitLab CI for CI CD and DevOps implementations.
  • You need to develop Infrastructure as code by writing AWS CDK scripts.
  • Consultancy to the stakeholders on AI ML (Artificial Intelligence & Machine Learning) and help build right solutions.
  • Support Test automation and deployment of the code base to the production environment.

Requirements

  • Bachelor's degree in one of the following fields: Computer science, mathematics, engineering, physics, or related. A Master's degree is considered a plus.
  • Preferably AWS or GCP Certifications in ML AI area.
  • Around 10 years of hands-on experience with ML / AI development and Operations.
  • Deep understanding with ML Life Cycle: Data Preprocessing, Training Pipeline, Inference Pipeline, Model monitoring, Post Processing as well as understanding of the MLOps.
  • Experience in developing, implementing, maintaining, and operating CI CD (Continuous Integration and Continuous Delivery) pipeline following the DevOps process.
  • Very good knowledge of Python coding and Linux administration.
  • Experience in working with JIRA and Confluence and Agile delivery model.
  • You are result-driven as well as excellent interpersonal, communication, and collaborative skills.
  • You are fluent in both spoken and written English.

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