AI Engineer

Edgecore Networks Corporation; Bengaluru; Presencial; INR 900.000 - 1.400.000; Jornada completa

Descripción de la vacante

Edgecore Networks Corporation in Bengaluru is seeking dynamic AI engineers to design, develop, and deploy advanced AI/ML solutions for edge devices. The role focuses on models like LLMs, diffusion models and vision transformers, with optimization and deployment on embedded hardware.

You will work on hyperparameter tuning, data pipelines, and integration with sensors and communication protocols, while leveraging Linux-based embedded platforms to deliver efficient, power-aware AI solutions.

Formación

• Experience in AI/ML model development and deployment.
• Hands-on experience with PyTorch, TensorFlow or similar.
• Knowledge of embedded systems and edge AI deployment.
• Familiarity with Linux-based systems and hardware integration.
• Strong analytical and problem-solving skills.

Responsabilidades

• Design, train, and optimize AI models for edge devices.
• Port and optimize models for embedded hardware (e.g., TensorRT, TFLite).
• Develop end-to-end AI pipelines on embedded Linux platforms.
• Perform model quantization, distillation, and PEFT techniques.
• Benchmark and profile performance on edge hardware.
• Integrate AI models with sensors, cameras, and actuators.
• Collaborate with hardware teams for deployment readiness.
• Establish data pipelines, including synthetic data generation and cleaning.
• Conduct hardware-in-the-loop testing and debugging.

Conocimientos

AI/ML model development

Edge device deployment

PyTorch

TensorFlow

Embedded Linux

Hardware integration

Herramientas

TensorRT

NCNN

TFLite

Descripción del empleo

Required Experience: 5 to 10 Years

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, diAusion 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-eAicient 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