Work Location: Anna University, Chennai — Department of Ceramic Technology Type: Full-Time Organization: Reneonix About the Project Reneonix is partnering with Anna University – Department of Ceramic Technology to develop next-generation foam glass materials for insulation, construction, and circular economy applications. The university’s Ceramic Technology Department will lead scientific formulation, research guidance, and material characterization, while Reneonix will execute on-ground development to bring the technology to pilot and commercial scale. This role is positioned as the full-time execution engineer working directly within Anna University’s environment. Role Overview The R&D Engineer will work closely with professors and researchers from Anna University to execute daily experiments, run furnace trials, prepare material batches, collect data, and support the scientific progress of the foam glass research program. Key Responsibilities Execute experimental plans provided by Anna University’s Ceramic Technology faculty. Prepare cullet powder, foaming agents, stabilizers, and batch mixes. Operate furnaces, sintering cycles, thermal profiles, and foaming trials. Maintain accurate lab records, experiment logs, and data sheets. Conduct basic material property testing (density, porosity, compression sample prep). Coordinate sample submissions for advanced testing at the university (SEM, XRD, TGA, DSC, etc.). Support prototype preparation, mold handling, and small-scale manufacturing trials. Maintain all relevant equipment, including furnaces, molds, mixers, and analytical tools. Act as the coordination bridge between Reneonix and Anna University for scheduling experiments, tracking progress, and communicating updates. Ensure adherence to safety, documentation, and research protocols. Qualifications B.Tech or M.Tech in Ceramic Technology, Materials Science, Chemical Engineering, Metallurgical Engineering, or related fields. 1–4 years of hands-on experience in ceramics, glass materials, thermal processing, or furnace-based research. Strong understanding of powder preparation, sintering, thermal cycles, and lab measurement techniques. Excellent documentation habits and attention to detail. Ability to work independently inside a university research environment while collaborating with both academic and industry teams. Curious, motivated, and eager to work in a high-intensity experimental research program. What This Role Offers Direct involvement in a university–industry deeptech research collaboration. Hands-on experience with real scientific innovation in foam glass. Opportunity to work closely with professors, researchers, and industry engineers. Potential to contribute to IP, publications, and early-stage product development.
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.