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Data Scientist - LLM/Generative AI

GAC Solutions
7 - 10 Years
Others

Posted on: 07/05/2026

Job Description

Key Responsibilities :


- Design, develop, and deploy LLM-based and GenAI solutions for real-world use cases


- Build RAG pipelines, LLM workflows, and AI-powered assistants


- Perform prompt engineering, model evaluation, and fine-tuning


- Develop and optimise advanced machine learning models for prediction and analytics


- Work with large-scale structured and unstructured datasets


- Build scalable inference systems and APIs for model deployment


- Integrate AI/ML solutions with existing products and data platforms


- Improve model performance, latency, and cost efficiency


- Collaborate closely with engineering and product teams to productionize AI features


- Monitor, evaluate, and continuously improve deployed models


What Were Looking For :


- Strong proficiency in Python and the ML ecosystem


- Hands-on experience in building LLM and Generative AI applications


- Expertise in prompt engineering, RAG architectures, embeddings, and vector search


- Experience with frameworks such as LangChain, LlamaIndex, or similar tools


- Familiarity with vector databases like FAISS, Milvus, or Pinecone


- Practical experience with PyTorch or TensorFlow


- Experience working with large-scale and distributed datasets


- Proven experience in deploying ML/AI models as APIs or production services


- Strong SQL and data analysis skills


- Understanding of ML lifecycle, evaluation, and monitoring


- Exposure to MLOps practices and experiment tracking tools


- Experience with cloud platforms (AWS/GCP/Azure) is preferred


- Familiarity with streaming or high-volume telemetry data systems is an added advantage


Ideal Candidate Profile :


- Has successfully deployed at least one LLM/GenAI solution in production


- Demonstrates a strong problem-solving and execution mindset


- Comfortable working in fast-paced, ambiguous environments


- Focused on scalable, practical AI solutions rather than just experimentation


- Able to translate business problems into effective AI-driven solutions


- Strong communication and collaboration skills

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