Orbion Infotech
Website:
orbioninfotech.com
Job details:
Primary Title: Principal AI/ML Architect A leader in the Information Technology & Services sector building enterprise-grade AI/ML platforms, intelligent automation, and data-driven products for global customers. We design scalable, secure, and production-ready ML systems that power business-critical decisioning across domains including finance, retail, and logistics. Location: Bangalore, India ? On-site role. This opportunity is for an experienced architect to lead model lifecycle design, production deployment, and cross-functional engineering of mission-critical AI services. Role & Responsibilities Define and own end-to-end AI/ML architecture for large-scale systems: model training, versioning, deployment, and monitoring. Design microservice-based inference platforms and CI/CD pipelines to deploy models with low-latency and high-availability guarantees. Lead cross-functional teams to translate business requirements into scalable data pipelines, feature stores, and production-ready ML models. Implement MLOps best practices: automated training, model validation, lineage, rollback, and observability. Evaluate and integrate open-source and cloud-native tooling (serving, monitoring, feature stores) to optimize cost, throughput, and reliability. Mentor engineers and establish engineering excellence playbooks for code quality, testing, security, and deployment standards. Skills & Qualifications Must-Have Python TensorFlow PyTorch Kubernetes Docker MLflow Preferred Kubeflow Apache Spark AWS SageMaker Qualifications: Proven track record (approx. 10 years) designing and delivering enterprise ML systems in production; strong system design background; experience with cloud providers and secure, compliant deployments. Benefits & Culture Highlights High-impact engineering culture with ownership of end-to-end solutions and opportunities to influence product strategy. Collaborative, fast-paced environment emphasizing engineering excellence, mentorship, and continuous learning. Competitive compensation, professional development support, and hands-on exposure to cutting-edge ML infrastructure.
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