AI/ML Engineer/ Python/GenAI Fullstack/ Data Scientist

As an experienced AI/ML Engineer, your role will involve designing, developing, and deploying cutting-edge solutions in Data Science, Deep Learning, and Generative AI. You will work on advanced AI frameworks, fine-tune LLMs, and implement responsible AI guardrails. Key Responsibilities: - End-to-end involvement in data curation, LLM fine-tuning, and deployment pipelines - Implement guardrails for responsible AI and ensure seamless serving of models - Work on SLM/LLM fine-tuning techniques: SFT, PEFT, LoRA, RLHF - Collaborate on MLOps frameworks for scalable AI solutions Qualifications Required: - Hands-on experience in Data Science, AI/ML, and Deep Learning domains - Strong expertise in Generative AI and related workflows - Proficiency in Python and experience with Linux/Windows environments - Familiarity with GenAI frameworks: LangChain, LlamaIndex, LangGraph, CrewAI, NeMo Agent Toolkit, NAT - Understanding of DL & GenAI algorithms: Transformers, CNN, RNN, etc. - Experience with NLP, Large Language Models (LLMs), and Multimodal Models like: GPT, LLaMa, Mistral, Qwen, Nemotron - Strong background in data science toolkits: TensorFlow, Keras, PyTorch, Pandas, NumPy - Exposure to Cloud platforms: Azure, AWS, or GCP - Experience with Git, Docker, Kubernetes, and MLOps frameworks Additionally, the company values strong problem-solving skills. As an experienced AI/ML Engineer, your role will involve designing, developing, and deploying cutting-edge solutions in Data Science, Deep Learning, and Generative AI. You will work on advanced AI frameworks, fine-tune LLMs, and implement responsible AI guardrails. Key Responsibilities: - End-to-end involvement in data curation, LLM fine-tuning, and deployment pipelines - Implement guardrails for responsible AI and ensure seamless serving of models - Work on SLM/LLM fine-tuning techniques: SFT, PEFT, LoRA, RLHF - Collaborate on MLOps frameworks for scalable AI solutions Qualifications Required: - Hands-on experience in Data Science, AI/ML, and Deep Learning domains - Strong expertise in Generative AI and related workflows - Proficiency in Python and experience with Linux/Windows environments - Familiarity with GenAI frameworks: LangChain, LlamaIndex, LangGraph, CrewAI, NeMo Agent Toolkit, NAT - Understanding of DL & GenAI algorithms: Transformers, CNN, RNN, etc. - Experience with NLP, Large Language Models (LLMs), and Multimodal Models like: GPT, LLaMa, Mistral, Qwen, Nemotron - Strong background in data science toolkits: TensorFlow, Keras, PyTorch, Pandas, NumPy - Exposure to Cloud platforms: Azure, AWS, or GCP - Experience with Git, Docker, Kubernetes, and MLOps frameworks Additionally, the company values strong problem-solving skills.