The client is looking for someone with short notice or notice serving candidates.

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Venue Details - 3rd Floor, Brilliant Titanium building, scheme no.78 , Vijay Nagar Indore .

• Design, develop, and fine-tune Generative AI models, including LLMs, GANs, VAEs, and Diffusion Models.
• Work with transformer-based architectures like GPT, BERT, and T5 for NLP applications.
• Optimize and fine-tune pre-trained foundation models (Llama, GPT, Falcon, etc.) for specific use cases.
• Develop AI-generated content applications, including text, image, video, and speech synthesis models.
• Utilize Reinforcement Learning with Human Feedback (RLHF) to improve AI-generated outputs.
• Deploy AI models using APIs, cloud platforms (AWS, GCP, Azure), and containerized environments (Docker, Kubernetes).
• Collaborate with data scientists, ML engineers, and software developers to integrate AI capabilities into applications.
• Implement prompt engineering, retrieval-augmented generation (RAG), and embedding techniques for better AI interactions.
• Stay updated with advancements in Generative AI, multimodal models, and responsible AI practices.

Requirements

• 5+ years of experience in AI/ML with a strong focus on Generative AI.
• Expertise in Python, TensorFlow, PyTorch, and Hugging Face Transformers.
• Hands-on experience with LLMs, GANs, VAEs, Diffusion Models, and NLP frameworks.
• Knowledge of vector databases (FAISS, Pinecone, Weaviate) for retrieval-based AI models.
• Strong understanding of deep learning architectures, embeddings, and fine-tuning techniques.
• Experience with MLOps, API development, and cloud-based AI deployments.
• Familiarity with AI safety, ethics, and bias mitigation strategies.
• Strong problem-solving and analytical skills with the ability to work on end-to-end AI solutions.
• Generative AI certifications (Google Generative AI Engineer, DeepLearning.AI) are a plus.

Skills: vaes,api development,generative ai,tensorflow,mlops,reinforcement learning with human feedback (rlhf),deep learning architectures,cloud platforms (aws, gcp, azure),embedding techniques,kubernetes,gans,bias mitigation,diffusion models,artificial intelligence,ai safety,hugging face transformers,vector databases (faiss, pinecone, weaviate),nlp,nlp frameworks,machine learning,docker,pytorch,llms,python,ethics