Senior ML Engineer: MLOps & Production (Remote India)

G10X Pte Ltd

United States

Remote

USD 31,000 - 62,000

Full time

2 days ago
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Job summary

We are seeking a Senior Machine Learning Engineer with strong hands-on MLOps experience to deploy and maintain production ML systems. The role emphasizes operationalizing models, monitoring performance, and managing lifecycle across multimodal data (vision, text, metadata).

You will build scalable PySpark and Databricks pipelines, leverage cloud platforms like AWS/Azure/GCP, and collaborate with cross-functional teams to deliver robust, production-ready ML solutions.

Qualifications

  • 5+ years of hands-on experience in Machine Learning / ML Engineering.
  • Strong hands-on MLOps and production ML deployment experience.
  • Experience with PySpark, Databricks, and Python in production ML systems.
  • Experience deploying Deep Learning models into production.
  • Solid understanding of the end-to-end MLOps lifecycle.
  • Experience with multimodal data (CV + text + metadata).
  • Experience with at least one cloud platform (AWS/Azure/GCP).

Responsibilities

  • Design, deploy, and operationalize Machine Learning and Deep Learning models in production.
  • Build and maintain end-to-end MLOps workflows including training, validation, deployment, monitoring, versioning, and retraining.
  • Develop scalable data and ML pipelines using PySpark and Databricks.
  • Productionize Deep Learning models and support scalable model inference.
  • Work with multimodal data (CV, text, metadata) to build ML solutions.
  • Implement model monitoring, performance tracking, drift detection, experiment tracking, and lifecycle management.
  • Collaborate with Data Scientists, ML Engineers, Data Engineers, and stakeholders to deliver production-ready ML solutions.
  • Ensure ML systems are scalable, reliable, maintainable, and suitable for production environments.
  • Work with cloud-based ML infrastructure and deployment platforms.

Skills

MLOps
Production ML deployment
End-to-end ML lifecycle
Cloud platforms (AWS/Azure/GCP)
Multimodal data (CV + text)
Model monitoring & drift detection
Python programming

Tools

PySpark
Databricks
Python

Job description

We are seeking a Senior Machine Learning Engineer with strong hands-on MLOps experience to deploy and maintain production ML systems. The role emphasizes operationalizing models, monitoring performance, and managing lifecycle across multimodal data (vision, text, metadata).

You will build scalable PySpark and Databricks pipelines, leverage cloud platforms like AWS/Azure/GCP, and collaborate with cross-functional teams to deliver robust, production-ready ML solutions.

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