AI Architect - Computer Vision Systems

Location & Employment

Location: Chennai, Tamil Nadu (Hybrid: Remote + On-site prototyping)

Employment Type: Full-time

Experience Level: 4+ years in AI/ML architecture

About Reneonix & The Role

Reneonix is innovating Recycling Infrastructure-as-a-Service focused on glass bottle collection and AI-powered real-time color sorting (clear, green, amber, blue, mixed) and quality inspection. We are looking for an AI Architect to design and build scalable computer vision solutions deployable on edge devices such as Jetson Nano and Raspberry Pi, achieving fast response times with under 30ms latency.

You will create the end-to-end AI system architecture, including multi-camera data ingestion, model selection, edge optimization, and integration with sorting hardware, to enable highly accurate, robust bottle identification and sorting in dynamic industrial environments.

Key Responsibilities:

Architect vision pipelines covering object detection, color classification, and defect analysis, incorporating advanced model architectures such as YOLO variants and segmentation networks.

Select and optimize AI models and inference frameworks (PyTorch, TensorFlow, ONNX, TensorRT) for sub-30ms latency inference on edge hardware.

Define and implement MLOps workflows for dataset management, model versioning, drift detection, and automatic retraining.

Address real-world variability in lighting, motion blur, and clutter on conveyor systems to maintain model robustness.

Lead the technical roadmap from prototype development through industrial deployment and scaling.

Collaborate with computer vision engineers on implementation and mentor junior members on system design principles.

Required Qualifications:

Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field.

4+ years of experience designing production AI/ML systems with at least 2 years focused on computer vision architectures such as object detection and semantic segmentation.

Expertise in Python, C++, deep learning frameworks (PyTorch, TensorFlow), computer vision libraries (OpenCV), and optimizing models for edge deployment (quantization, pruning, TensorRT, OpenVINO).

Strong systems design knowledge including real-time ML processing, multi-camera fusion, and working within hardware and latency constraints.

Experience with Docker, Kubernetes, and building scalable model serving pipelines is a plus.

Portfolio or GitHub demonstrating deployed vision AI projects, preferably in industrial or recycling contexts.

Preferred Skills

Domain knowledge of recycling, waste sorting, or glass processing systems.

Hands-on experience with embedded AI platforms like NVIDIA Jetson Nano/Orin, Raspberry Pi Compute Module.

Familiarity with 3D vision, pose estimation, or multispectral imaging techniques.

Proficiency with MLOps tools such as MLflow, Kubeflow, or Weights & Biases.

What We Offer

• Direct impact on environmental sustainability by advancing circular economy technologies.
• High ownership in a fast-paced startup environment with access to leadership.
• Competitive salary package with equity options for early team members.
• Flexible hybrid work model and prototyping hardware budget provided.