Generative ai engineer

Company: Nexoria TechworksLocation: Bangalore, Hyderabad, Pune, NoidaExperience: 3+ YearsEmployment Type: Full-Time, Onsite/HybridAbout Nexoria TechworksNexoria Techworks is a rapidly growing technology company focused on building intelligent, scalable, and high-impact digital solutions powered by Artificial Intelligence. We work on cutting-edge innovations across AI, automation, and data-driven systems that help organizations accelerate digital transformation. Our mission is to create next-generation AI-driven platforms that deliver measurable business outcomes.We are now expanding our AI team and looking for an experienced Generative AI Engineer with strong hands-on experience in building and deploying advanced generative models and LLM-based applications.Role OverviewThe Generative AI Engineer will be responsible for designing, training, and optimizing AI models that generate text, images, audio, or other content. This role requires a strong understanding of deep learning architectures, NLP systems, transformer-based models, and their application to real-world problems. The ideal candidate should have prior experience implementing and scaling generative models in production environments.Key Responsibilities- Design, develop, and fine-tune Generative AI models such as Large Language Models (LLMs), diffusion models, or transformers for text, image, or multimodal outputs.- Build Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Chroma.- Develop and implement prompt engineering strategies and optimization frameworks for task-specific outputs.- Collaborate with the product and engineering teams to integrate AI models into scalable systems and APIs.- Conduct research and experimentation on state-of-the-art generative architectures including GPT, LLa MA, Mistral, and Stable Diffusion.- Develop automation pipelines using Lang Chain, Hugging Face Transformers, or equivalent frameworks.- Deploy and monitor models using cloud platforms such as AWS, GCP, or Azure, ensuring performance, reliability, and cost-efficiency.- Implement MLOps practices for model training, evaluation, deployment, and lifecycle management.- Collaborate closely with data engineers and scientists for data collection, preprocessing, and feature engineering.- Document model architectures, training methodologies, and deployment strategies for internal knowledge sharing.Required Technical Skills- Proficiency in Python and experience with AI/ML frameworks like Py Torch, Tensor Flow, or JAX.- Strong understanding of transformer-based architectures and deep learning fundamentals.- Hands-on experience with LLMs (GPT, LLa MA, Falcon, Claude, Mistral, etc.) and API integration.- Familiarity with Lang Chain, Hugging Face Transformers, and vector search systems (FAISS, Pinecone, Chroma, Milvus).- Experience in building and optimizing prompt-based systems and custom model fine-tuning.- Working knowledge of cloud infrastructure and Dev Ops tools (AWS S3, EC2, Lambda, Docker, Kubernetes).- Proficiency with MLOps tools such as MLflow, DVC, or Weights & Biases.- Understanding of data security, scalability, and API versioning principles.- Bonus: Experience in text-to-image (Stable Diffusion, DALL·E) or text-to-speech/speech-to-text systems (Whisper, Eleven Labs).Preferred Qualifications- Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline.- Minimum of 3 years of experience in machine learning or AI, with at least 1 year in Generative AI or NLP.- Proven track record of building and deploying AI models into production.- Strong problem-solving and analytical skills, with the ability to apply research into practical product implementations.- Portfolio, Git Hub repositories, or research publications demonstrating prior AI/ML projects will be an added advantage.