Role Overview
We are seeking a highly skilled and innovative AI Model Architect to lead the development and refinement of our core AI models.
You will be responsible for the post-training optimization, fine-tuning, and reinforcement learning strategies that drive the performance and efficiency of our AI-powered automation solutions.
This role is critical in ensuring our models are robust, scalable, and deliver exceptional accuracy and value to our clients.
You will be a key technical leader, shaping the future of our AI capabilities.
Qualifications
· 5+ years of experience in AI/Machine Learning model development and deployment.
· Deep understanding of foundational model architectures (e.g., Transformers, LLMs, Diffusion Models).
· Proven experience in post-training techniques such as quantization, pruning, and knowledge distillation.
· Strong expertise in fine-tuning large language models (LLMs) and other foundational models for specific downstream tasks.
· Solid understanding of reinforcement learning algorithms (e.g., Proximal Policy Optimization, Deep Q-Networks) and their applications.
· Proficiency in model evaluation metrics and benchmarking techniques.
· Strong programming skills in Python and experience with deep learning frameworks (TensorFlow, PyTorch).
· Experience with cloud-based machine learning platforms (AWS SageMaker, Google Vertex AI, Azure Machine Learning).
· Master’s or PhD in Computer Science, Artificial Intelligence, or related field.
· Excellent communication and collaboration skills.
· Experience with distributed training and model parallelism.
· Experience with model serving and deployment infrastructure (e.g., TensorFlow Serving, TorchServe).
· Experience with data augmentation and synthetic data generation techniques.
· Publications in leading AI/Machine Learning conferences or journals.
· Experience with techniques to improve model interpretability and explainability.