Data scientist - Gen AI, AI/ML

4 years

0 Lacs

Posted:5 days ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Contractual

Job Description

Hi Everyone Role : Data Scientist - Gen AI, AI/ML Exp - 4+yr Shift : General IST 8 hour shift Position Type : Remote & Contractual JD : About the Role: We are seeking a passionate and results-driven Data Scientist with deep expertise in Artificial Intelligence, Machine Learning, and Generative AI (GenAI) . In this role, you will work at the intersection of data science and cutting-edge AI technologies to build intelligent systems, drive automation, and unlock business value from data. Key Responsibilities: Design, develop, and deploy AI/ML models and GenAI-based applications to solve real-world business problems. Conduct data wrangling, preprocessing, feature engineering, and advanced analytics. Build NLP, computer vision, recommendation, or predictive models using traditional and deep learning methods. Collaborate with cross-functional teams including product managers, data engineers, and software developers. Stay current with advancements in AI/ML and apply best practices to improve existing systems. Design and evaluate LLM-based pipelines , prompt engineering strategies, and fine-tuning approaches. Present insights and results to stakeholders in a clear and actionable manner. Work on cloud-based ML pipelines (AWS/GCP/Azure) and MLOps frameworks for deployment and monitoring. Key Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field. 4+ years of experience in data science and machine learning . Strong hands-on skills in Python , SQL , and ML libraries like scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers . Proficiency in GenAI use cases (text generation, summarization, image generation, etc.) and LLMs (OpenAI GPT, BERT, etc.). Experience with prompt engineering , RAG pipelines , LangChain , or vector databases is highly desirable. Strong understanding of data structures, algorithms, and model evaluation techniques. Exposure to cloud platforms (AWS/GCP/Azure) and containerization tools like Docker, Kubernetes is a plus. Excellent communication and problem-solving skills. Show more Show less

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