Senior AI Developer

Key Responsibilities

• Model Development: Design, train, and validate advanced AI and machine learning models tailored for specific business and hardware constraints.

• GPU Optimization: Optimize model inference and execution speeds using CUDA and CuML to maximize hardware utilization.

• Embedded Deployment: Implement and deploy AI models onto resource constrained embedded systems and edge devices.

• Pipeline Integration: Develop, test, and maintain robust, end-to-end modules for data pre-processing and output post-processing.

• Performance Tuning: Profile and benchmark AI workloads to minimize latency, power consumption, and memory footprint.

• Collaboration: Work closely with hardware and software engineering teams to integrate AI modules into production-ready systems. 

Required Skills & Qualifications

• Experience: 5–7 years of professional, hands-on experience in AI/ML development.

• Core Language: Expert-level proficiency in Python.

• Accelerated Computing: Strong working knowledge of NVIDIA CUDA for parallel computing and GPU acceleration.

• Machine Learning Libraries: Proven experience using CuML (RAPIDS) for accelerated machine learning pipelines.

• Embedded AI: Direct experience deploying AI models on embedded hardware (e.g., NVIDIA Jetson, ARM-based platforms).

• Software Engineering: Solid understanding of data structures, algorithms, and writing clean, maintainable code. 

Preferred Qualifications

• Experience with Deep Learning frameworks (PyTorch, TensorFlow).

• Familiarity with model optimization tools like TensorRT or ONNX.

• Knowledge of C++ for embedded systems integration