Gen AI Engineer (Walk-in drive on Mar 29)

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

Your profile must be submitted through Cognisol to get POC details to enter this walk-in.

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