Job Summary

We are seeking an innovative Generative AI Data Scientist to join our AI and Data Science team. In this role, you will research, design, build, and deploy cutting-edge Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), multimodal AI, and advanced machine learning techniques. You will collaborate with cross-functional teams to create intelligent AI-powered applications that enhance business operations, automate workflows, and improve customer experiences.

The ideal candidate has strong expertise in machine learning, deep learning, natural language processing (NLP), prompt engineering, vector databases, and cloud-based AI platforms. You will play a key role in evaluating, fine-tuning, and optimizing foundation models while ensuring responsible AI practices, security, scalability, and production readiness.

Key Responsibilities

• Design, develop, and deploy Generative AI applications using Large Language Models (LLMs).
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.
• Fine-tune open-source and commercial foundation models for domain-specific use cases.
• Develop AI-powered chatbots, virtual assistants, copilots, and intelligent automation solutions.
• Create scalable prompt engineering strategies to improve model accuracy and performance.
• Develop data preprocessing, feature engineering, and model evaluation pipelines.
• Integrate vector databases for semantic search and knowledge retrieval.
• Evaluate model performance using automated benchmarks and human feedback.
• Optimize AI inference performance, latency, and operational costs.
• Collaborate with software engineers to deploy AI models into production environments.
• Implement Responsible AI principles, including fairness, explainability, and governance.
• Monitor deployed models for performance degradation, hallucinations, and model drift.
• Conduct experiments to improve reasoning, summarization, classification, and content generation.
• Stay current with emerging AI research, foundation models, and industry best practices.
• Document technical solutions, research findings, and implementation guidelines.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related field.
• 6+ years of experience in Data Science, Machine Learning, or Artificial Intelligence.
• Hands-on experience building Generative AI or LLM-based applications.
• Strong understanding of supervised and unsupervised machine learning algorithms.
• Experience deploying machine learning models into production.
• Strong programming skills in Python.
• Experience working with structured and unstructured datasets.
• Knowledge of cloud-based AI services and distributed computing.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline.
• Experience with multimodal AI (text, image, audio, and video).
• Familiarity with AI agents and autonomous workflow orchestration.
• Experience building enterprise-scale AI platforms.
• Knowledge of AI governance, privacy, and security best practices.
• Contributions to open-source AI projects or published AI research.

Technical Skills

Programming Languages

• Python
• SQL
• Scala (preferred)
• R (preferred)

Machine Learning & Deep Learning

• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM
• Hugging Face Transformers

Generative AI & LLM Technologies

• GPT models
• Llama
• Mistral
• Claude
• Gemini
• LangChain
• LlamaIndex
• DSPy
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents

Vector Databases

• Pinecone
• Weaviate
• Milvus
• Chroma
• FAISS

NLP Technologies

• spaCy
• NLTK
• Sentence Transformers
• Tokenization
• Embeddings
• Semantic Search

Cloud Platforms

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

MLOps & Deployment

• MLflow
• Docker
• Kubernetes
• GitHub Actions
• Jenkins
• Kubeflow
• Ray

Data Technologies

• Apache Spark
• Databricks
• Snowflake
• BigQuery
• PostgreSQL

Visualization & Analytics

• Power BI
• Tableau
• Matplotlib
• Plotly

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate
• NVIDIA Certified AI Professional
• Microsoft Certified: Azure Data Scientist Associate

Soft Skills

• Strong analytical and critical thinking
• Research mindset with a passion for innovation
• Excellent communication and presentation skills
• Cross-functional collaboration
• Problem-solving and decision-making
• Ability to mentor junior team members
• Adaptability in a rapidly evolving AI landscape
• Business acumen and strategic thinking

What You’ll Do

• Build next-generation Generative AI products and intelligent enterprise applications.
• Develop scalable LLM solutions for business automation and decision support.
• Create AI-powered copilots, assistants, and knowledge management systems.
• Improve enterprise productivity through advanced AI capabilities.
• Collaborate with engineering, product, and research teams to deliver production-ready AI solutions.
• Drive innovation using state-of-the-art Generative AI technologies while ensuring responsible and secure AI deployment.