Scalable Machine Learning Infrastructure Specialist

2 days ago

Bengaluru, Karnataka, India beBeeMachineLearning Full time ₹ 12,00,000 - ₹ 24,00,000

Job Title: Scalable Machine Learning Infrastructure Specialist

Job Description:

We are seeking an experienced professional to design and maintain scalable, reliable, and automated machine learning infrastructure on Google Cloud Platform (GCP). As a key member of our team, you will work closely with Data Scientists, Data Engineers, and Business SMEs to deploy ML models and pipelines in production, ensuring reproducibility, governance, and monitoring at scale.

Key Responsibilities:
  1. Build and maintain ML pipelines using Vertex AI Pipelines and Terraform for infrastructure-as-code (IaC).
  2. Develop and manage CI/CD pipelines for model training, deployment, and monitoring using Cloud Build, Git, and Cloud Source Repositories.
  3. Packaging and deploying ML models with Docker on GKE (Google Kubernetes Engine) or Cloud Run.
  4. Implement robust logging, monitoring, and alerting using Cloud Monitoring and Cloud Logging.
  5. Design reusable templates for experimentation, model serving, and orchestration.
  6. Automate data source integration, especially with BigQuery.
  7. Define and enforce ML lifecycle governance from experimentation through decommissioning.
Requirements:

To succeed in this role, you should have the following qualifications:

  1. 5+ years of experience in MLOps, ML Engineering, or Data Engineering roles.
  2. Proven expertise in GCP services like Vertex AI, BigQuery, Cloud Storage, and Cloud Functions.
  3. Strong hands-on experience with Python, Terraform, CI/CD tools (e.g., GitHub Actions, Cloud Build), Docker, and Kubernetes.
  4. Experience with full ML model lifecycle management, including experimentation tracking, monitoring, and versioning.
  5. Familiarity with MLOps best practices: reproducibility, automation, governance, and scalability.
Nice to Have:

The following skills would be beneficial for your success:

  1. Exposure to Kubeflow, MLflow, or similar MLOps platforms.
  2. Experience working in regulated industries (e.g., BFSI, Healthcare) with audit/compliance requirements.
  3. Background in time series forecasting or other complex ML workflows.
Why Join Us:

As a valued member of our team, you will enjoy:

  • Working with a cutting-edge ML stack in a cloud-first, automation-driven environment.
  • Collaborating with top talent in AI, cloud, and data engineering.
  • Being part of a company that prioritizes innovation, governance, and scalable machine learning.

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