ML Platform Engineer in India at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a ML Platform Engineer in India.

This role focuses on designing and building scalable machine learning platforms that power end-to-end ML and GenAI workflows for enterprise-grade systems. You will be responsible for architecting robust infrastructure that supports model training, deployment, monitoring, and lifecycle management across complex cloud environments. Working within a highly technical and collaborative engineering organization, you will bridge the gap between data science and production engineering. The position requires deep expertise in cloud-native systems, DevOps practices, and ML workflows to ensure reliable, secure, and efficient platforms. You will contribute to enabling data scientists and engineers to build, deploy, and scale models seamlessly. This is a high-impact role supporting Fortune 500 clients, where platform reliability and scalability are critical to success.

In this role, you will be responsible for designing, building, and optimizing end-to-end machine learning platforms that enable scalable and efficient ML operations across the organization.

• Architect and implement scalable MLOps platforms supporting the full machine learning lifecycle
• Design and maintain automated pipelines for data processing, model training, deployment, and monitoring
• Evaluate and integrate appropriate cloud services (AWS, GCP, or Azure) for ML workloads, with a preference for Azure
• Implement infrastructure as code, CI/CD pipelines, and containerized deployments using Docker and Kubernetes
• Enable version control for code, data, and machine learning models to ensure reproducibility
• Build tools and interfaces that support data scientists in efficiently using the ML platform
• Ensure system scalability, reliability, security, and compliance with industry standards
• Optimize platform performance, cost efficiency, and operational stability
• Implement monitoring, logging, and alerting systems for ML workflows and infrastructure
• Collaborate with data scientists, engineers, and stakeholders to align platform capabilities with business needs

This position requires strong experience in cloud engineering and machine learning infrastructure, along with the ability to design and operate scalable ML platforms in enterprise environments.

• 10+ years of experience in software engineering with strong exposure to cloud-based applications
• Proven experience building machine learning platforms using cloud services (Azure preferred)
• Strong expertise in cloud platforms such as AWS, GCP, or Azure, including ML and data services
• Hands-on experience with DevOps practices, CI/CD pipelines, and infrastructure as code
• Proficiency in containerization and orchestration tools such as Docker and Kubernetes
• Strong programming skills in Python and other ML-relevant languages
• Solid understanding of ML workflows, model training, deployment, and lifecycle management
• Experience with data engineering concepts including ETL pipelines and data storage systems
• Strong system design skills for scalable and distributed architectures
• Knowledge of security, compliance, and best practices for ML systems
• Experience with monitoring, logging, and observability tools for production systems
• Ability to collaborate effectively with cross-functional teams including data scientists and engineers

• Fully remote work model with flexible engagement (FTE opportunity)
• Opportunity to work on enterprise-scale ML and GenAI platforms for global clients
• Exposure to advanced cloud-native architectures and MLOps best practices
• High-impact role shaping end-to-end machine learning infrastructure
• Collaborative, cross-functional engineering environment
• Competitive compensation aligned with senior-level expertise
• Opportunity to work with cutting-edge AI and machine learning technologies
• Career growth in large-scale platform engineering and AI systems