AI Engineer

About the job

Job Summary We are seeking an AI Engineer who is passionate about Artificial Intelligence, Embedded Systems, and Edge AI products. The role involves working across the entire AI lifecycle—from data collection and labeling to model deployment, MLOps, and ... product testing on real hardware platforms such as ESP32, Raspberry Pi, and NVIDIA Jetson. Key Responsibilities AI & Machine Learning ● Assist in developing, training, and evaluating ML / Deep Learning models ● Work on Computer Vision and sensor-based AI applications ● Perform data preprocessing, cleaning, labeling, and augmentation ● Collect real-world data from cameras, sensors, and IoT devices ● Optimize AI models for latency, accuracy, and edge deployment MLOps & Deployment ● Assist in deploying models using Docker, APIs, and edge AI pipelines ● Monitor model performance and assist in continuous improvement ● Help maintain model lifecycle workflows (training → testing → deployment) Embedded Systems & ECE Integration ● Work with ESP32 microcontrollers for data acquisition and control ● Interface AI systems with electronic hardware, sensors, cameras, and actuators ● Understand and debug hardware–software integration Product Testing & Validation ● Perform functional testing and validation of AI-based products ● Test AI models under real-world environmental conditions ● Assist in system reliability, performance benchmarking, and bug fixing ● Support field testing and on-device debugging Required Qualifications ● Bachelor’s degree in Electronics & Communication Engineering (ECE) or related field ● Strong understanding of: ○ Digital Electronics ○ Basic communication concepts ● Programming skills in Python ● Hands-on or academic experience with Edge devices ● Familiarity with Linux-based systems ● Basic understanding of Machine Learning & AI concepts Mandatory Technical Skills ● ESP32 programming (Arduino / ESP-IDF basics) ● Python for: ○ Data handling ○ Automation scripts ● Data labeling and dataset management ● Linux command-line usage ● Understanding of AI model training and inference workflows Preferred / Good-to-Have Skills ● Computer Vision: OpenCV ● ML frameworks: PyTorch / TensorFlow ● Edge AI tools: TensorRT, DeepStream, ONNX ● MLOps tools: Docker, Git, basic CI/CD concepts ● Experience with: ○ Raspberry Pi / NVIDIA Jetson ○ Camera sensors & electronic modules ● Basic cloud or API integration knowledge Who Should Apply ● ECE graduates interested in AI + Electronics + Embedded Systems ● Candidates with AI + hardware projects ● Freshers eager to work on end-to-end AI product development ● Engineers interested in edge AI, IoT, and real-world deployments What We Offer ● Hands-on experience with production AI systems ● Exposure to MLOps, embedded AI, and product lifecycle ● Opportunity to work with real hardware and real data ● Mentorship and structured learning environment ● Growth path into AI Engineer / Embedded AI Engineer / MLOps roles

Requirements

• AI & Machine Learning
• MLOps & Deployment
• Embedded Systems
• Python programming
• ESP32 programming
• Computer Vision

Qualifications

• Bachelor’s degree in Electronics & Communication Engineering (ECE) or related field

Preferred Technologies

• AI & Machine Learning
• MLOps & Deployment
• Embedded Systems
• Python programming
• ESP32 programming
• Computer Vision

Benefits

• Hands-on experience with production AI systems
• Exposure to MLOps, embedded AI, and product lifecycle
• Opportunity to work with real hardware and real data
• Mentorship and structured learning environment
• Growth path into AI Engineer / Embedded AI Engineer / MLOps roles