Job Description

Overview:

Join the Prodapt team in building AI/ML Solutions. If you have 5 - 10 years of experience & would like to work on a cutting-edge ML platform, enabling efficient analysis, testing, and decision-making at scale.
Responsibilities:
Design, develop, and maintain simulation services and tools for ML feature, model, and rule evaluation. Build and optimize data pipelines for point-in-time historical data access and feature backfilling. Containerize and deploy ML models and services using Docker and Seldon on Kubernetes clusters. Integrate with Client's cloud infrastructure (GCP) and internal APIs for seamless simulation workflows. Collaborate with data scientists, ML engineers, and QA to deliver robust, scalable solutions. Contribute to CI/CD pipelines and DevOps practices for automated testing, deployment, and monitoring. Write clean, maintainable, and well-documented code using Python and related SDKs. Participate in code reviews, design discussions, and platform architecture decisions. Troubleshoot, debug, and optimize simulation jobs and platform services.

Requirements:

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or related field. Proficiency in Python and experience with ML/AI model development. Hands-on experience with Docker for containerization and Seldon for model deployment. Familiarity with Kubernetes for orchestration and cloud platforms (preferably GCP). Experience with Git for version control and collaborative development. Strong understanding of APIs, microservices, and distributed systems. Experience with CI/CD and DevOps tools for ML workflows. Ability to work in a fast-paced, collaborative environment and communicate effectively.

Preferred Qualifications

Experience with feature engineering, backfilling, and point-in-time data access. Familiarity with large-scale financial/ML platforms. Experience with Jupyter Notebooks and AI SDKs. Knowledge of MLOps best practices, including monitoring, model versioning, and automation. * Exposure to big data technologies and scalable data processing.