Senior Data Scientist - AI & GenAI
Posted Updated
Summary
Senior Data Scientist in Hyderabad designing and deploying production AI/GenAI solutions — RAG pipelines, assistants, forecasting, and regulatory knowledge bases — while owning the end-to-end ML lifecycle. Core stack includes Python, SQL, ML/NLP, and cloud AI platforms (Vertex AI, SageMaker/Bedrock, Azure AI).
Senior Data Scientist - AI GenAI
Job Summary
Key Responsibilities
Required Skills Experience
Good to Have
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Location: Hyderabad, India
Experience: 9-12 Years
Experience: 9-12 Years
Job Summary
We are looking for Senior Data Scientist to design, build, and deploy advanced AI solutions across machine learning, Generative AI, and agentic workflows. The role involves solving complex business and regulatory challenges through scalable, secure, and production-ready AI applications.
Key Responsibilities
- Develop machine learning, GenAI, and agentic AI solutions, including RAG pipelines, assistants, classification, forecasting, and recommendation systems.
- Build AI solutions for regulatory filing support and searchable knowledge bases.
- Develop domain-specific knowledge bases for regulatory intelligence, competitive insights, and customer sentiment.
- Manage the end-to-end AI lifecycle, including data preparation, modeling, evaluation, deployment, monitoring, and CI/CD.
- Implement document processing, retrieval strategies, prompt engineering, and safe tool-use mechanisms.
- Define evaluation metrics, test datasets, A/B testing, and model drift monitoring.
- Apply responsible AI practices, including privacy, fairness, bias mitigation, security, and governance.
- Collaborate with business stakeholders, architects, data teams, and platform engineers to deliver measurable business value.
Required Skills Experience
- 9-12 years of relevant experience in data science and applied AI.
- Strong Python, SQL, statistical modeling, and machine learning skills.
- Experience with deep learning frameworks such as PyTorch or TensorFlow preferred.
- Strong understanding of the end-to-end ML lifecycle, model evaluation, deployment, and monitoring.
- Experience with NLP, Generative AI, embeddings, RAG, hybrid search, and prompt engineering.
- Knowledge of document processing, OCR, metadata management, and PII detection or redaction.
- Experience with cloud AI platforms such as Google Vertex AI, AWS SageMaker/Bedrock, or Azure AI Services.
- Understanding of enterprise AI governance, privacy, compliance, and responsible AI practices.
- Strong communication skills and the ability to translate technical outcomes into business impact.
Good to Have
- Vector databases
- LangChain
- LangGraph
- LlamaIndex
- RAG evaluation frameworks
- MLflow
- Peft/lora
- synthetic data generation
- AI agent development
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Skills
- A/B Testing
- Agentic AI
- AI
- AWS
- Azure
- CI/CD
- Cloud
- Data Science
- Deep Learning
- Embeddings
- Generative AI
- LangChain
- LangGraph
- LlamaIndex
- Machine Learning
- Metadata Management
- MLflow
- Model Evaluation
- NLP
- PEFT
- Prompt Engineering
- Python
- PyTorch
- Recommendation Systems
- SageMaker
- SQL
- TensorFlow
- Vector Databases
- Vertex AI