Applied Data Scientist (Generative AI)

Job Summary

IBM is seeking an Applied Data Scientist specializing in Generative AI to design, develop, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs). The role focuses on transforming business challenges into scalable AI products using machine learning, natural language processing, and Generative AI technologies. IBM’s data and analytics teams work on responsible AI adoption and enterprise AI solutions across cloud environments.

Job Description

As an Applied Data Scientist (Generative AI), you will:

• Develop and fine-tune Large Language Models (LLMs) for enterprise applications.
• Build intelligent AI assistants, chatbots, and knowledge management systems.
• Design and implement Retrieval-Augmented Generation (RAG) architectures.
• Create end-to-end machine learning and Generative AI pipelines.
• Work with structured and unstructured data to generate actionable insights.
• Deploy scalable AI solutions on cloud platforms.
• Collaborate with engineering, product, and business teams to deliver AI-driven innovations.
• Evaluate and optimize model performance, accuracy, and reliability.
• Implement responsible AI practices, governance, and model monitoring frameworks. Generative AI, LLMs, and production-grade AI deployment have become core requirements in modern data science roles.

Key Responsibilities

Generative AI Development

• Fine-tune foundation models and LLMs.
• Implement prompt engineering strategies.
• Develop conversational AI and AI agents.

Data Science & Machine Learning

• Build predictive and prescriptive analytics models.
• Perform data preprocessing and feature engineering.
• Conduct experimentation and model evaluation.

Enterprise AI Solutions

• Design RAG systems using vector databases.
• Integrate AI solutions with business applications.
• Develop scalable AI APIs and microservices.

Deployment & MLOps

• Deploy models using Docker and Kubernetes.
• Implement CI/CD pipelines for AI applications.
• Monitor model performance and automate retraining.

Collaboration & Leadership

• Partner with stakeholders to identify AI opportunities.
• Translate business requirements into technical solutions.
• Present findings and recommendations to leadership teams.

Required Technical Skills

• Programming: Python, SQL, PySpark
• Machine Learning: Scikit-learn, XGBoost, TensorFlow, PyTorch
• Generative AI: LLMs, Prompt Engineering, Fine-Tuning, AI Agents
• Frameworks: LangChain, LlamaIndex, Hugging Face
• RAG Systems: Vector Databases, Semantic Search, Embeddings
• Cloud Platforms: AWS, Azure, Google Cloud Platform
• Big Data: Apache Spark, Databricks, Hadoop
• MLOps: MLflow, Docker, Kubernetes, CI/CD
• Databases: PostgreSQL, MongoDB, Pinecone, ChromaDB

Preferred Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, or a related field.
• 3–7+ years of experience in Data Science, Machine Learning, or AI Engineering.
• Hands-on experience with Generative AI applications and LLM deployment.
• Strong understanding of NLP, deep learning, and distributed computing.
• Excellent communication and problem-solving skills.

Benefits

✅ Competitive Salary + Annual Bonus
✅ Stock Options and Performance Incentives
✅ Health, Dental, and Vision Insurance
✅ Hybrid/Remote Work Opportunities
✅ Learning and Certification Programs
✅ Generative AI and Cloud Training