SKILLS_ROADMAP

Engineering Competence Matrix

Technical proficiencies evaluated via system-level debugging, hardware programming, and model implementations.

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C++

90%

Real-time systems development, ROS2 nodes, memory management, and hardware interfaces.

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Python

95%

AI/ML prototyping, computer vision pipelines, scripting, and data analysis.

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ROS2

85%

Workspace setup, pub/sub architecture, custom interfaces, tf2 transforms, Nav2, and micro-ROS.

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System Design

80%

Distributed communication topologies, concurrency, state-machine designs, and sensor telemetry structures.

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Computer Vision

85%

LiDAR point cloud analysis, OpenCV filters, object detection, and sensor fusion.

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TypeScript

75%

Next.js dashboard interfaces, real-time WebSockets UI, and serial data visualizers.

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Linux

90%

Ubuntu Server, bash scripting, systemd service configuration, and edge device setup.

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Machine Learning

80%

TensorFlow, PyTorch, YOLOv8 inference optimization, and deep learning for robot vision.

METRIC_SOURCE: PRACTICAL_DEPLOYMENT_REPOS
AUTO_CALIBRATION: ACTIVE [TOLERANCE +/- 2.5%]