JOB DESCRIPTION:

We are looking for US based SMEs having experience in designing and developing educational content for AI & ML for one of our US based clients.

POSITION OVERVIEW:

We are looking for an experienced and forward-thinking Subject Matter Expert (SME) in Artificial Intelligence and Machine Learning to lead strategic initiatives related to intelligent agents, advanced language models, and modern ML model selection. In this role, you will guide cross-functional teams on best practices in applying AI to complex tasks, focusing on areas such as agent-based system design, zero/few-shot learning, and optimal model selection frameworks. Your insights will help shape AI solutions that are scalable, efficient, and cutting-edge.

REQUIREMENTS:

• Deep knowledge of machine learning theory, including model evaluation, generalization, and optimization.
• Proven expertise in language models and their practical deployment (e.g., DeepSeek, OpenAI APIs, Hugging Face).
• Strong familiarity with zero-shot/few-shot learning paradigms, prompt engineering, and NLP applications.
• Experience advising on or designing agent-based systems (e.g., LLM agents, planning agents, LangChain/AutoGPT architectures).
• Ability to translate complex ML concepts into clear, actionable guidance for technical and non-technical stakeholders.
• Excellent communication and presentation skills.

PREFERRED QUALIFICATIONS:

• Prior experience as an AI/ML consultant, researcher, or strategist.
• Academic or published contributions in areas related to machine learning, NLP, or agent systems.
• Exposure to enterprise-level AI deployments and model lifecycle management.
• Advanced degree (Master’s or PhD) in Machine Learning, AI, Data Science, or related field.

• Provide expert-level guidance on designing and deploying AI agents capable of reasoning, planning, and acting autonomously in complex environments.
• Advise data science and product teams on selecting the right machine learning models for different use cases and data types.
• Offer strategic input on leveraging zero-shot and few-shot learning to reduce training overhead and accelerate development cycles.
• Evaluate and recommend LLMs (e.g., DeepSeek, GPT, Claude) for specific applications, including performance benchmarking and prompt design.
• Conduct technical reviews and contribute to high-level solution architectures for ML-powered systems.
• Keep teams informed on the latest trends in AI, including emerging agent frameworks, foundational models, and research directions.