Design, develop, and deploy machine learning and generative AI models to address business needs.
Work with large-scale datasets using Python, SQL, and industry-standard libraries (Scikit-learn, TensorFlow, PyTorch, Keras, AutoML, etc.).
Develop and fine-tune LLM-based solutions (GPT-3, GPT-4, or similar models) for real-world applications.
Ensure data quality, integrity, and compliance with best practices, frameworks, and coding standards.
Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI-driven solutions.
Explore and apply natural language processing (NLP) techniques for text understanding, summarization, and sentiment analysis.
Implement solutions on cloud platforms (Azure, AWS, or GCP) ensuring scalability and efficiency.
Research and experiment with GenAI, Agentic AI models, and advanced frameworks to drive innovation.
Preferred candidate profile
Prior experience in building or fine-tuning LLM applications.
Familiarity with NLP techniques and tasks (NER, sentiment analysis, summarization, text classification).
Exposure to AutoML frameworks and cloud AI services (Azure AI, AWS SageMaker, GCP Vertex AI).
Experience with MLOps practices for model lifecycle management.
Strong problem-solving, communication, and collaboration skills in multidisciplinary environments.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full time