Job Description
About the Role:
Seeking a highly skilled ML Engineer with an experience of 4 years to join our dynamic team.
Requirements
- Sound understanding of deep learning fundamentals and architectures (CNNs, RNNs, Transformers, GANs, MoE).
- Proficiency in Python and experience with deep learning frameworks (TensorFlow, PyTorch, Keras).
- Experience with designing, training, fine-tuning and optimizing deep learning models, including LLMs, for various applications.
- Should have experience in applying fine-tuning techniques such as full fine-tuning, LoRA/QLoRA, prompt tuning, adapter layers and instruction tuning for task and domain adaptation.
- Exposure in developing and integrating AI agents capable of reasoning, planning and tool usage for enterprise workflows.
- Familiarity in preprocess, clean and augment large datasets for model training and evaluation.
- Expertise in implement models using frameworks such as TensorFlow, PyTorch and Hugging Face Transformers.
- Experience in evaluating models with relevant metrics (accuracy, BLEU, ROUGE, perplexity, etc.) and iterate for improvement.
- Knowledge of cloud platform GCP and GPU-based training.
- Familiarity with MLOps tools and workflows- cloud schedulers, cloud function, vertex ai pipelines, pub/sub for model training , deployment and monitoring.
- Experience in deploying models into production environments (cloud, on-premise, or hybrid) and monitor performance.
- Should set up and manage deployment pipelines using Git, CI/CD workflows, Tekton and GKE clusters for on-premises deployment.
- Research and implement cutting-edge techniques in deep learning, LLM training, and agent architectures.
- GCP ML certification will be preferred.
