DevOps Engineer

4 years

4 - 5 Lacs

Posted:5 hours ago| Platform: GlassDoor logo

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Work Mode

On-site

Job Type

Part Time

Job Description

The DevOps Engineer will be responsible for implementing our AI/ML initiatives across product development and business productivity improvements. This role focus on MLOps, infrastructure, cloud technologies, and Generative AI tools, collaborating across corporate teams and business-specific stakeholders to ensure seamless alignment with organizational objectives.

Major Responsibilities:

  • Implement DevOps best practices to optimize software development and deployment processes and update those best practices documentation.
  • Design, deploy, and manage scalable Cloud infrastructure using AWS or Azure platforms.
  • Support the implementation and tracking of DevOps maturity to drive continuous improvement.
  • Apply Agile process knowledge to enhance workflow management and team collaboration.
  • Collaborate with development teams to enhance the CI/CD pipeline and cloud-based solutions.
  • Design, and implement AI/ML infrastructure on cloud platforms (such as AWS, Azure), ensuring scalability, security, reliability and optimization for ML workloads.
  • Design, and build MLOps pipelines including model training, validation, and deployment using industry-standard tools and platforms.
  • Collaborate with data scientists/software engineers to implement AI/ML workflows.
  • Implement security best practices for AI/ML infrastructure and data management at scale.
  • Evaluate technologies by Analysis of Alternatives and implement Proof of Concepts to quickly validate before implementation.

Basic Qualifications:

  • Bachelor's or master’s degree in computer science, Engineering, or a related field with minimum of 4+ years hands-on experience in DevOps and MLOps roles.
  • Hands-on experience in scripting languages such as Shell, Perl, or Python.
  • Hands on experience in AWS or Azure Cloud platforms
  • Experience with AWS-specific tools such as SageMaker, Cloud Formation
  • Familiarity with open-source MLOps tools such as MLflow, Kubeflow, or TensorFlow, extended (TFX) for managing ML workflows and model lifecycles.
  • Experience with Generative AI tools and frameworks.
  • Knowledge of AI/ML frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn. Understanding of data management and ETL processes as well as handling large and diverse datasets.
  • Excellent communication, interpersonal and problem-solving skills and ability to work independently and collaboratively.
  • Adaptability to new technologies and methodologies.

Desired:

  • Certifications in relevant technologies or platforms.
  • Experience in the Energy or Industrial IoT sectors.
  • Embrace the GE Vernova Way of Working principles:
    • Innovation: Contribute to creative solutions and advancements in technology.
    • Customers: Focus on delivering outstanding value and service.
    • Lean: Apply efficient processes to maximize productivity.
    • One Team: Collaborate effectively across diverse teams and disciplines.
    • Accountability: Take responsibility for achieving excellence in all tasks and projects.

Additional Information

Relocation Assistance Provided: No

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