Job Description

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

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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

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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.