Responsibilities :
- Design, develop, and deploy AI / ML models for real-world applications.
- Work with NLP, deep learning, and traditional ML algorithms.
- Develop end-to-end ML pipelines.
- Optimize model performance using hyperparameter tuning.
- Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, and other frameworks.
- Work with structured and unstructured data, performing data wrangling and feature extraction.
- Deploy models in cloud environments (AWS, Azure, or GCP) using tools like SageMaker or Vertex AI.
- Collaborate with cross-functional teams to integrate AI models into production.
- Ensure scalability, performance, and efficiency of AI / ML solutions.
- Stay updated with emerging AI trends and technologies.
Required Skills :
Strong experience in machine learning, deep learning, NLP, and AI model development.Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models.Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs).Hands-on experience with computer vision (CNNs, OpenCV, YOLO).Solid understanding of ML model deployment and MLOps (Docker, Kubernetes).Experience with cloud platforms (AWS, Azure, GCP) for AI / ML model deployment.Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks).Familiarity with API development using Django, Flask, or FastAPI.Preferred Skills :
Experience with AI-powered chatbots and OpenAI API integration.Exposure to LLMs (GPT, LLaMA, Falcon, etc.) and generative AI models.Skills Required
Deep Learning, Python, Nlp, Computer Vision, MLops, Tensorflow