
Data Scientist
3 days ago
Role Overview :
We are seeking a highly skilled Data Scientist Generative AI Specialist to design, develop, and optimize next-generation AI solutions. The ideal candidate will have hands-on expertise in Generative AI, Agentic AI, LLMs, and NLP, along with a strong background in MLOps and cloud-based AI deployments. This role will focus on building intelligent, scalable AI systems leveraging advanced frameworks, orchestration tools, and cloud services.
Key Responsibilities :
- Design, develop, and deploy generative AI solutions, including LLM-based systems, RAG pipelines, and agentic AI applications.
- Build and optimize prompt engineering strategies, knowledge graphs, embeddings, and semantic search pipelines.
- Implement and manage vector databases (e.g., FAISS, Redis) for scalable search and retrieval tasks.
- Leverage Azure AI tools (Azure OpenAI, Cognitive Services, Azure ML) and orchestration frameworks (e.g., LangChain, Agentic AI frameworks).
- Fine-tune and deploy models using Hugging Face, OpenAI APIs, and related AI platforms.
- Collaborate with engineering teams to integrate AI applications using FastAPI, Databricks, AWS, and MLflow.
- Establish and maintain CI/CD pipelines for ML models, ensuring seamless MLOps and DevOps integration.
- Debug, optimize, and continuously improve AI pipelines, deployments, and end-user performance.
- Stay updated with the latest advancements in AI research, tools, and frameworks.
Required Skills & Qualifications :
- 3+ years of proven experience in Data Science, with a focus on Generative AI, LLMs, NLP, and Agentic AI.
- Hands-on expertise in RAG pipelines, knowledge graphs, embeddings, and semantic search.
- Strong development skills in Python for AI/ML application development.
- Experience with Azure AI tools (Azure OpenAI, Cognitive Services, Azure ML).
- Proficiency in LangChain, Hugging Face, and agentic AI orchestration frameworks.
- Solid experience with MLOps, CI/CD pipelines, AI deployment optimization, and DevOps practices.
- Familiarity with FastAPI, Databricks, AWS, MLflow, Faiss, Redis, and OpenAI APIs.
- Strong problem-solving, debugging, and optimization mindset.
Preferred Qualifications :
- Prior contributions to AI/ML research or open-source projects.
- Experience building enterprise-grade AI solutions for production.
- Knowledge of scalable system design for AI-driven applications.
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