Artificial Intelligence Engineer

Edgecore Networks India; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Edgecore Networks India is seeking an AI Engineer to design, develop, and deploy AI/ML solutions on embedded edge hardware. You will work with LLMs, diffusion models, and vision transformers, focusing on optimization and deployment on edge devices.

The role emphasizes model fine-tuning, quantization, PEFT, and integration with hardware components, including sensors and communication protocols. Strong Linux and embedded systems experience is required.

Qualifications

• Strong experience in AI/ML model development and deployment.
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow, etc.).
• Knowledge of embedded systems and edge AI deployment.

Responsibilities

• Design, develop, and train AI models for edge devices and embedded platforms.
• Perform model optimization, quantization, distillation, and PEFT techniques.
• Build and manage large-scale data pipelines, including synthetic data generation and augmentation.
• Port and deploy AI models on embedded hardware using TensorRT, NCNN, and TFLite.
• Develop end-to-end AI pipelines on embedded Linux (Yocto/OpenWRT/custom NOS).
• Integrate AI models with sensors, cameras, actuators, and communication protocols (CAN, Modbus, MQTT, ROS2).
• Conduct hardware-in-the-loop testing, debugging, and performance profiling.

Skills

AI model development

PyTorch

Embedded systems

Edge AI deployment

Linux

Hardware integration

Education

Bachelor's degree in CS/EE

Tools

TensorRT

NCNN

TFLite

Edge TPU

Yocto

Job description

Job Title: AI Engineer

Company: Edgecore Networks
Location: North Bangalore Cluster (Near Hebbal / Manyata Tech Park)

Required Experience: 5 to 10 Years
Open Positions: 5

Job Summary:

We are looking for dynamic and skilled AI Engineers to design, develop, and deploy advanced AI/ML solutions for real-world applications. The role involves working on cutting-edge technologies including large language models, computer vision, and embedded AI systems, with a strong focus on optimization and deployment on edge devices.

Key Responsibilities:

• Design, develop, and train custom AI models such as LLMs, diffusion models, and vision transformers for specific use cases.
• Perform model fine-tuning, quantization, distillation, and optimization using techniques like LoRA, QLoRA, and PEFT.
• Conduct hyperparameter tuning, ablation studies, and benchmarking to improve model performance.
• Build and manage large-scale data pipelines, including synthetic data generation, data augmentation, and data cleaning.
• Port, deploy, and optimize AI models on embedded hardware using frameworks such as TensorRT, NCNN, TFLite, and Edge TPU.
• Develop end-to-end AI pipelines on embedded Linux platforms (Qualcomm Linux, Yocto, OpenWRT, or custom NOS).
• Implement inference acceleration, memory optimization, and power-efficient AI solutions.
• Integrate AI models with hardware components such as sensors, cameras, actuators, and communication protocols (CAN, Modbus, MQTT, ROS2).
• Perform hardware-in-the-loop testing, debugging, and performance profiling.

Required Skills & Qualifications:

• Strong experience in AI/ML model development and deployment
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow, etc.)
• Knowledge of embedded systems and edge AI deployment
• Experience with model optimization techniques and performance tuning
• Familiarity with Linux-based systems and hardware integration
• Strong analytical and problem-solving skills

Contact Details:

Email: [e-mail]
WhatsApp: [phone]