Description

You will design and build the architecture for generative AI systems capable of autonomous reasoning and decision-making.

Responsibilities

• Design AI infrastructure and mechanisms for data storage, processing, and retrieval to ensure scalability and efficiency.
• Develop and implement machine learning, deep learning, and neural network algorithms.
• Train and fine-tune models using supervised, unsupervised, or reinforcement learning techniques.
• Design deep learning architectures for NLP, computer vision, and predictive analytics.
• Integrate AI components into existing software platforms and ensure seamless communication between modules.
• Manage data integration workflows, including collection, cleansing, and transformation.

Required Skills

• 5+ years of experience in AI system design and development.
• Bachelor's or master's degree in Computer Science, Artificial Intelligence, or a related field.
• Expertise with Large Language Models (LLMs) and prompt engineering.
• Proficiency in Python, R, or Java.
• Hands-on experience with TensorFlow, PyTorch, or Keras.
• Experience deploying models on cloud platforms including AWS, Azure, or Google Cloud.
• Deep understanding of neural networks, machine learning, and deep learning methodologies.
• Experience designing large-scale AI solutions and data integration pipelines.

Preferred Skills

• Knowledge of NVIDIA CUDA, cuDNN, TensorRT, and the NVIDIA GPU stack.
• Understanding of HPC, AI workloads, and Big Data platforms like Hadoop or Spark.
• Knowledge of ethical AI practices and laws.

Key Skills

Education

bachelor's or master's degree or equivalent in computer science