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Ronald Nap
Intern Machine Learning & AI Engineer specializing in computer vision and ML systems
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About
Robotics/ML engineer with internship experience at Valeo building a deep-learning prototype to replace parts of a legacy SLAM backend for autonomous parking, focused on making models run reliably in real time on embedded hardware (quantization/distillation + TensorRT). Also brings strong MLOps/deployment experience (Docker, Kubernetes on AWS EKS, CI via GitHub Actions) and has supported patent filing by explaining the technical approach to legal stakeholders.
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Key Strengths
- Optimized deep learning models for embedded real-time robotics using quantization/distillation and TensorRT
- Systematic SLAM debugging using recorded run replay, intermediate-signal logging, and root-cause isolation
- Improved robustness in challenging conditions (low light, motion blur, repetitive textures) via guardrails and threshold tuning
- Regression validation across scenarios to prevent fixes from breaking other behaviors
- Production-oriented deployment experience: containerized ML services and deployed on Kubernetes (AWS EKS) with autoscaling and performance testing
- Built CI regression pipelines with GitHub Actions to protect internal tooling workflows
- Able to communicate complex technical ideas cross-functionally (supported patent process with legal team)
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Publications
1 publication
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