Job Title:Edge AI Specialist
Company Name: Quantum Pulse Technologies
Job Type: Full-Time (On-site / Hybrid)
Experience Level: 3 to 5 Years
Job Overview
Quantum Pulse Technologies is seeking a high-performing Edge AI Specialist to join our team at the SECE Innovation Hub, Coimbatore. In this role, you will be responsible for translating complex deep learning and machine learning models into lightweight, highly optimized AI applications capable of running locally on resource-constrained embedded devices, single-board computers, and custom hardware targets. Located inside the technology hub at Sri Eshwar College of Engineering, you will collaborate with cross-functional software, hardware, and robotics teams to deploy real-time computer vision, signal processing, and predictive AI workloads to the edge.
Key Responsibilities
- Edge Model Optimization: Quantize (INT8/FP16), prune, compress, and compile deep learning models for low-latency, low-power execution on edge hardware.
- On-Device Deployment: Deploy trained models onto edge accelerators and microcontrollers using frameworks like TensorRT, TensorFlow Lite, OpenVINO, and ONNX Runtime.
- Hardware-Software Co-Design: Benchmark, profile, and tune deep learning inference pipelines across CPUs, GPUs, NPUs, and DSPs to meet strict real-time and thermal constraints.
- Data Pipeline &Preprocessing: Build efficient C++/Python data ingestion and preprocessing pipelines for real-time video, audio, and multi-modal sensor streams.
- System Integration: Work closely with embedded system and firmware engineers to integrate Edge AI runtimes into production firmware, Linux environments, or RTOS setups.
- Model Validation & Testing: Monitor accuracy-versus-latency trade-offs on target physical hardware and refine quantization-aware training (QAT) pipelines as necessary.
- Field Deployment &MLOps: Establish automated edge deployment, continuous monitoring, and remote model updating protocols for deployed devices.
- Architected internal project requirements and facilitated high-impact training programs to upskill enthusiastic internal talent.
Required Skills & Qualifications
Core Technical Skills:
- Experience: 3 to 5 years in machine learning, computer vision, or embedded software engineering, with a focus on on-device deployment.
- Programming Languages: Proficiency in C++ (Modern C++14/17) and Python.
- AI/ML Frameworks: Practical experience with PyTorch or TensorFlow for training and fine-tuning neural networks.
- Edge Frameworks & Compilers: Operational experience with TensorRT, TensorFlow Lite, ONNX Runtime, OpenVINO, or STM32Cube.AI.
- Hardware Platforms: Hands-on experience deploying AI on platforms such as NVIDIA Jetson (Nano/Orin), Google Coral TPU, Raspberry Pi, or NPU/ARM Cortex-based SoCs.
- Optimization Techniques: Deep knowledge of post-training quantization (PTQ), quantization-aware training (QAT), model pruning, and structural distillation.
- OS & Tools: Experience working in Linux environments (Ubuntu, Yocto), Git, Docker, and hardware profiling tools.
Soft Skills:
- Strong problem-solving abilities and aptitude for low-level performance debugging.
- Strong team player capable of bridging the gap between data science teams and embedded software engineers.
- Excellent written and verbal communication skills.
Preferred / Good-to-Have Skills
- Experience with real-time video streaming pipelines (GStreamer, DeepStream, or OpenCV acceleration).
- Familiarity with TinyML for low-power microcontrollers (STM32, ESP32, or Nordic BLE SoCs).
- Exposure to Edge MLOps platforms for over-the-air (OTA) model updates and fleet monitoring.
Benefits & Work Environment
- Working inside the technology ecosystem of the SECE Innovation Hub, Coimbatore.
- Competitive salary aligned with industry standards.
- Access to specialized hardware labs, prototyping kits, and modern edge compute resources.
Pay: ₹850,000.00 - ₹1,400,000.00 per year
Benefits:
Work Location: In person
