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Responsibilities

• The project focuses on designing, building, and operating a scalable internal platform for Machine Learning and AI services
• The goal is to enable reliable training, deployment, and inference of ML/AI models on our own cloud-native infrastructure

Profile

• Strong hands-on experience with Machine Learning and AI workloads
• Extensive practical experience running ML/AI workloads on Kubernetes (production-grade)
• Solid MLOps expertise, including:
• Model lifecycle management
• CI/CD for ML models
• Monitoring, logging, and reproducibility
• Experience with ML and AI inference systems, focusing on scalability and low latency
• Excellent knowledge of Kubernetes-based infrastructure for ML (GPU scheduling, scaling, reliability)
• Experience with NVIDIA Triton Inference Server (strong plus / highly preferred)
• Ability to design, build, and operate self-managed ML/AI infrastructure

Benefits

• A very renowned company

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