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MLOPS Solution Architect with GCP

1 month ago


India RED Global Full time

Hi,


Hope you all are doing well.

At present one of our customers is in need of an MLOPS Solution Architect with GCP & AI for a initial 6-12 month contract role for a Remote opportunity .


We are seeking a talented and experienced GCP Solution Architect/Engineer/Lead with a strong background in MLOps to join our team. The ideal candidate will be responsible for designing, implementing, and optimizing cloud-based solutions that support machine learning workflows on Google Cloud Platform (GCP). You will collaborate with cross-functional teams to ensure the successful deployment and scaling of machine learning models.


Key Responsibilities:


  • Design and implement scalable, secure, and reliable architectures on GCP for machine learning applications.
  • Develop and manage end-to-end MLOps pipelines, including data preprocessing, model training, validation, and deployment.
  • Collaborate with data scientists, engineers, and stakeholders to understand business requirements and translate them into technical solutions.
  • Optimize cloud resources for performance, cost efficiency, and security.
  • Provide guidance on best practices for GCP services related to machine learning, such as AI Platform, BigQuery, Cloud Functions, and Kubernetes Engine.
  • Monitor and troubleshoot ML models in production, ensuring high availability and performance.
  • Stay current with industry trends and emerging technologies in GCP and MLOps.


Qualifications:


  • Bachelor’s degree in Computer Science, Information Technology, or a related field (Master’s preferred).
  • Proven experience as a Solution Architect with a focus on GCP and MLOps.
  • Strong understanding of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).
  • Proficiency in GCP services, particularly those relevant to machine learning and data engineering.
  • Experience with containerization technologies (Docker, Kubernetes).
  • Familiarity with CI/CD practices and tools related to ML workflows.
  • Excellent problem-solving skills and ability to work collaboratively in a team environment.
  • Strong communication skills to articulate technical concepts to non-technical stakeholders.