Lead Engineer

1 day ago


Guindy National Park, India Prodapt Solutions Full time

Overview:

Join the Prodapt team in building the Model Automation Platform—a unified, cloud-native system that streamlines and automates the entire model development lifecycle. You will help design, develop, and optimize a scalable platform that enables rapid onboarding, training, evaluation, and governance of machine learning models across business units.

Responsibilities:

  • Design, develop, and maintain automation pipelines for model training, evaluation, and deployment using Kubernetes and GCP.
  • Build and enhance the unified web UI for managing model development, logging, evaluation, and dataset creation.
  • Integrate CI/CD pipelines for automated model refresh, versioning, and lifecycle management.
  • Develop and manage database-backed systems for storing model metadata, training datasets, and automation manifests.
  • Implement and optimize pipeline/template systems for workflow automation and onboarding new models.
  • Ensure robust separation and monitoring of research and production environments.
  • Develop dashboards for monitoring model refreshes, training jobs, and automation statistics.
  • Automate model logging, including source code, parameters, metrics, and datasets for governance and reproducibility.
  • Collaborate with data scientists, ML engineers, and platform teams to deliver scalable, reliable solutions.
  • Participate in code reviews, architecture discussions, and continuous improvement of the platform

Requirements:

Required Technical Skills
  • Proficiency in Python and experience with ML/AI model development (TensorFlow, PyTorch, scikit-learn, MLflow).
  • Experience with Kubernetes and Google Cloud Platform (GCP) for orchestration, compute, and storage.
  • Hands-on experience with CI/CD tools and automation of ML workflows.
  • Strong understanding of database systems for metadata and artifact management.
  • Familiarity with web UI development and integration (React, Angular, or similar frameworks).
  • Experience with containerization (Docker) and cloud-native deployment patterns.
  • Knowledge of model governance, logging, and reproducibility best practices.
  • Excellent troubleshooting, debugging, and communication skills.
Preferred Qualifications
  • Experience with agentic frameworks (LangChain, CrewAI) and LLM integration.
  • Familiarity with large-scale financial/ML platforms.
  • Experience with pipeline/template management systems and workflow automation.
  • Exposure to model security, vulnerability scanning, and compliance automation.
  • Knowledge of monitoring, metrics, and dashboarding tools.

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