Artificial Intelligence Architect - AWS SageMaker (8-14 yrs)

Responsibilities :

AI Research & Optimization :

- Continuously research and evaluate the latest AI models and techniques.

- Optimize cloud and custom AI engines to enhance performance and efficiency.

- Implement model optimization techniques such as quantization and pruning.

Model Development & Deployment :

- Develop, train, and fine-tune AI models using TensorFlow and PyTorch.

- Deploy AI models using cloud-based AI services like AWS SageMaker, Azure ML, and Google Vertex AI.

Programming & Performance Tuning :

- Develop high-performance code in Python, CUDA, and TensorRT for AI acceleration.

- Implement distributed computing solutions using Spark or Ray.

Cloud & MLOps Expertise :

- Design and manage AI infrastructure on cloud platforms.

- Implement containerization and orchestration using Docker and Kubernetes.

- Optimize AI workloads for performance, scalability, and reliability.

Problem-Solving & Research :

- Apply strong analytical and problem-solving skills to address complex AI challenges.

- Explore and evaluate emerging AI technologies and trends.

- Drive the development of innovative AI-driven solutions.

- Contribute to the AI community by publishing research papers in reputable conferences and journals.

Qualifications :

- 8-14 years of experience in AI/ML development and architecture.

Key Skills :

- AI Model Development (TensorFlow, PyTorch)

- Cloud AI Services (AWS SageMaker, Azure ML, Google Vertex AI)

- AI Model Optimization (Quantization, Pruning)

- Python Programming

- CUDA

- TensorRT

- Distributed Computing (Spark, Ray)

- Cloud Platforms (AWS, Azure, GCP)

- Docker & Kubernetes

- MLOps

- Research & Problem-Solving