Lead Machine Learning Engineer for Scalable Infrastructure Solutions

Shape the future of AI in dentistry as a Machine Learning Engineer. You will build the production backbone for robust, scalable services using advanced GPU and infrastructure technologies.

This systems-level engineering role focuses on transforming research models into reliable, production-grade services. With over 5 years of experience in ML Infrastructure or MLOps, you will optimize GPU workloads and design fault-tolerant infrastructures. Your hands-on expertise in Docker and asynchronous job systems will ensure seamless deployment and robust service delivery.

Key Responsibilities :

• Convert research models to scalable inference services
• Design reproducible Docker environments for deployment
• Optimize GPU memory usage for 3D workloads
• Architect asynchronous job orchestration for GPU resources
• Build CI / CD pipelines and automate deployment workflows

Requirements

• 5+ years in ML Infrastructure or MLOps
• Proven success in deploying ML models in production
• Strong expertise in Docker management
• Experience with GPU workloads and orchestration
• Familiarity with backend APIs integration

Elevate AI applications by bridging research and production, delivering impactful solutions in modern dentistry.

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