Ai Ml Engineer

Key Responsibilities:

• Design, train, and deploy machine learning and deep learning models based on business requirements.
• Evaluate ML models using appropriate performance metrics.
• Work with NLP (Natural Language Processing), LLMs (Large Language Models), Computer Vision, and Speech-to-Text models.
• Implement models like LLama, Falcon, BERT, T5 Transformer, and Hugging Face models.
• Develop machine learning solutions for classification, regression, and clustering tasks.
• Utilize libraries such as NumPy, Pandas, Matplotlib, SpaCy, Scikit-learn, TensorFlow, and PyTorch.
• Write efficient Python code and work with tools like Google Colab, Jupyter Notebook, and AWS SageMaker.
• Monitor data drift and retrain models as needed based on outcomes and evolving data.
• Deploy models on AWS, with hands-on experience in AWS services like SageMaker, EC2, ECS, and Kubernetes.
• Solve complex analytical problems with a strong problem-solving approach.

Good to Have:

• Experience with LangChain or LLamaIndex.
• Familiarity with RAG-based application development.
• Hands-on experience with GCP services for model deployment.