AI Engineer

About the Role
At Arqaios, we are building the next generation of sensor-driven smart fixtures that enable safety and automation in homes. As a Computer Vision / AI Engineer, you will be responsible for turning depth data and radar signals into actionable human understanding, the foundation of our fall detection MVP and future automation hub.

Key Responsibilities

• Develop pipelines using ZED 2i SDK for human skeleton/keypoint extraction (18+ points).
• Implement multi-sensor fusion combining mmWave radar signals (gait, velocity, presence) with depth-based skeletal data.
• Train and fine-tune ML models for fall detection, activity recognition, and human identity verification.
• Build adaptive pipelines that continuously learn from in-home environments.
• Benchmark models for accuracy, latency, and edge-device feasibility.

Minimum Experience: 2–4 years in computer vision, AI, or robotics (or equivalent strong academic/research experience).

• Entry bar: At least 2 years hands-on with computer vision pipelines, skeleton extraction, or multi-sensor perception (internships, grad school research, or industry).
• Stronger candidates: 4+ years building production-ready CV/AI systems, ideally with edge deployment experience.

Required Skills & Qualifications

• Strong background in Computer Vision and AI, with hands-on experience using PyTorch/TensorFlow.
• Proficiency with OpenCV and real-time data processing.
• Experience with Kalman filtering, sensor fusion, or pose estimation.
• Familiarity with Human Activity Recognition (HAR) datasets.
• Solid understanding of model deployment best practices (MLOps, evaluation metrics).

Preferred / Plus Points

• Experience with ZED SDK, 3D vision, or depth cameras.
• Exposure to edge AI optimizations (TensorRT, ONNX).