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Zensar Technologies - Generative AI Application Developer - LLM/RAG Job Opening In Pune – Now Hiring Zensar Technologies

Zensar Technologies Generative AI Application Developer LLM/RAG

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Job description

<p><p><b>Position : </b> Generative AI Application Developer<br/><br/><b>Experience : </b> 7-16 years<br/><br/><b>Location : </b> Bangalore, Hyderabad, and Pune, India<br/><br/><b>Notice Period : </b> Early joiners are highly appreciated.</p><p><br/></p><p><b>Job Summary : </b><br/><br/></p><p>We are seeking a highly skilled and experienced Generative AI Application Developer to architect, develop, and deploy production-grade AI systems.

The ideal candidate will possess deep technical expertise in the end-to-end lifecycle of Generative AI models, with a strong focus on building scalable and robust applications.

This role requires a hands-on developer who can translate complex business challenges into innovative solutions using Large Language Models (LLMs) and other generative Responsibilities : Development & Fine-Tuning : </b></p><p><br/></p>- Design, build, and train Generative AI models and algorithms using deep learning techniques.<br/><br/></p><p>- Implement and fine-tune Large Language Models (LLMs) using custom datasets to meet specific business requirements.<br/><br/></p><p>- Apply techniques such as Retrieval-Augmented Generation (RAG) and prompt engineering to enhance model performance and reduce Engineering & Preparation : </b></p><p><br/></p>- Architect and implement data pipelines for the ingestion, preprocessing, and transformation of large datasets.<br/><br/></p><p>- Manage and optimize vector databases for efficient semantic search and information Development & Integration : </b></p><p><br/></p>- Develop robust, scalable applications that integrate Generative AI models using APIs and microservices.<br/><br/></p><p>- Build prototypes and demonstrate proof-of-concepts (POCs) to technical and business stakeholders.<br/><br/></p><p>- Ensure seamless integration of AI applications with existing enterprise & MLOps : </b></p><p><br/></p>- Deploy and manage AI models in production environments using MLOps principles.<br/><br/></p><p>- Implement CI/CD pipelines for continuous integration and deployment of machine learning code.<br/><br/></p><p>- Monitor model performance, latency, and resource utilization & Innovation : </b></p><p><br/></p>- Stay current with the latest advancements in Generative AI, deep learning, and transformer architectures.<br/><br/></p><p>- Evaluate and experiment with new models, frameworks, and tools to drive Skills : : </b></p><p><br/></p><p>- Expert-level proficiency in Python.<br/><br/></p><p>- Strong experience with software engineering fundamentals, including object-oriented programming, data structures, and Expertise : </b><br/><br/></p><p>- Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.<br/><br/></p><p>- Hands-on experience with Generative AI models (e.g., GANs, VAEs) and architectures (e.g., Transformers, diffusion models).<br/><br/></p><p>- Proven experience with Large Language Models (LLMs), fine-tuning, RAG, and prompt & Cloud : </b></p><p><br/></p>- Strong experience with cloud platforms for AI/ML (AWS SageMaker, Azure ML, or GCP Vertex AI).<br/><br/></p><p>- Familiarity with MLOps tools like MLflow, Kubeflow, or DVC.<br/><br/></p><p>- Experience with containerization technologies like & APIs : </b></p><p><br/></p>- Experience with vector databases such as Pinecone, ChromaDB, or FAISS.<br/><br/></p><p>- Proficient in SQL and knowledge of NoSQL databases.<br/><br/></p><p>- Experience with building and consuming RESTful APIs and : </b></p><p><br/></p>- Hands-on experience with key libraries such as Hugging Face Transformers, LangChain, or Engineering Practices : </b></p><p><br/></p>- Strong knowledge of version control systems, especially Skills : </b></p><p><br/></p>- Experience developing SaaS products or consumer-facing applications powered by Generative AI.<br/><br/></p><p>- Knowledge of specific cloud-native services like AWS Bedrock, Azure OpenAI Service, or GCP's Vertex AI Model Garden.<br/><br/></p><p>- Familiarity with other programming languages such as Java or C++ for high-performance computing.<br/><br/></p><p>- Experience with UI/UX frameworks (React, Angular) to build user interfaces for AI applications.<br/><br/></p><p>- Contributions to open-source projects in the AI or machine learning community.<br/><br/></p><p>- Relevant cloud certifications (AWS Certified Machine Learning Specialty).</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations


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