G
Data Scientist
GLBAI Solutions PVT LTD
Required Skills
Communication Python SQLJob Description
Global AI Solutions – Hiring: Data Scientist (NLP, Generative AI & Agentic AI)
Location: Remote/Hybrid
Employment Type: Full-Time | Permanent
Experience: 1–2 Years | Immediate Joiners Preferred
We are seeking a highly skilled and motivated Data Scientist / AI Engineer with hands-on experience in Natural Language Processing (NLP) and Generative AI, including Retrieval-Augmented Generation (RAG) and Agentic AI Systems.
The ideal candidate should possess a deep understanding of machine learning algorithms, large language model (LLM) orchestration, and deployment pipelines, with a strong foundation in mathematical and statistical principles.
Key Responsibilities
- Design, develop, and deploy machine learning and deep learning models for NLP and Generative AI use cases.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines — integrating embeddings, vector databases, and retrieval frameworks.
- Develop Agentic AI systems using frameworks like LangChain, LangGraph, enabling dynamic multi-step reasoning and autonomous task execution.
- Implement and fine-tune LLMs for specific business tasks (chatbots, summarization, document Q&A, workflow automation, etc.).
- Integrate AI models into production environments using FastAPI or similar frameworks for RESTful API development.
- Collaborate cross-functionally with engineering and product teams to translate requirements into scalable and maintainable AI solutions.
- Maintain and query databases (PostgreSQL, MongoDB, SQL) with a focus on pg_vector for high-performance vector search and retrieval.
- Continuously research and apply the latest innovations in Generative AI, RAG systems, Agentic AI architectures, and LLM frameworks.
- Ensure quality, reliability, and scalability of AI systems through performance monitoring and iterative optimization.
🎯 Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Proven experience (3 years) in machine learning model development and deployment.
- Strong programming skills in Python, with expertise in libraries such as TensorFlow, PyTorch, and scikit-learn.
- Practical knowledge of LangChain, LangGraph, and pg_vector for building intelligent RAG/Agentic pipelines.
- Proficiency with SQL, PostgreSQL, and MongoDB for data storage and management.
- Solid understanding of deep learning architectures, embeddings, and language model fine-tuning.
- Experience in developing and deploying APIs using FastAPI or equivalent frameworks.
Additional Skills (Good to Have)
- Experience with MLOps tools (Docker, Git, CI/CD pipelines, model monitoring).
- Familiarity with LLM orchestration, multi-agent systems, or workflow automation frameworks.
📩 How to Apply
If you are passionate about AI innovation, love solving complex challenges with Generative AI, RAG, and Agentic systems, and want to be part of a cutting-edge AI team — we’d love to hear from you.
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Location: Remote/Hybrid
Employment Type: Full-Time | Permanent
Experience: 1–2 Years | Immediate Joiners Preferred
We are seeking a highly skilled and motivated Data Scientist / AI Engineer with hands-on experience in Natural Language Processing (NLP) and Generative AI, including Retrieval-Augmented Generation (RAG) and Agentic AI Systems.
The ideal candidate should possess a deep understanding of machine learning algorithms, large language model (LLM) orchestration, and deployment pipelines, with a strong foundation in mathematical and statistical principles.
Key Responsibilities
- Design, develop, and deploy machine learning and deep learning models for NLP and Generative AI use cases.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines — integrating embeddings, vector databases, and retrieval frameworks.
- Develop Agentic AI systems using frameworks like LangChain, LangGraph, enabling dynamic multi-step reasoning and autonomous task execution.
- Implement and fine-tune LLMs for specific business tasks (chatbots, summarization, document Q&A, workflow automation, etc.).
- Integrate AI models into production environments using FastAPI or similar frameworks for RESTful API development.
- Collaborate cross-functionally with engineering and product teams to translate requirements into scalable and maintainable AI solutions.
- Maintain and query databases (PostgreSQL, MongoDB, SQL) with a focus on pg_vector for high-performance vector search and retrieval.
- Continuously research and apply the latest innovations in Generative AI, RAG systems, Agentic AI architectures, and LLM frameworks.
- Ensure quality, reliability, and scalability of AI systems through performance monitoring and iterative optimization.
🎯 Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Proven experience (3 years) in machine learning model development and deployment.
- Strong programming skills in Python, with expertise in libraries such as TensorFlow, PyTorch, and scikit-learn.
- Practical knowledge of LangChain, LangGraph, and pg_vector for building intelligent RAG/Agentic pipelines.
- Proficiency with SQL, PostgreSQL, and MongoDB for data storage and management.
- Solid understanding of deep learning architectures, embeddings, and language model fine-tuning.
- Experience in developing and deploying APIs using FastAPI or equivalent frameworks.
Additional Skills (Good to Have)
- Experience with MLOps tools (Docker, Git, CI/CD pipelines, model monitoring).
- Familiarity with LLM orchestration, multi-agent systems, or workflow automation frameworks.
📩 How to Apply
If you are passionate about AI innovation, love solving complex challenges with Generative AI, RAG, and Agentic systems, and want to be part of a cutting-edge AI team — we’d love to hear from you.
7 three 8 seven 9 four 0 none 6 five