We are seeking an experienced Machine Learning to join our AI-driven project. The ideal candidate will have a strong background in prompt engineering techniques such as Tree of Thought (ToT) and Chain of Thought (CoT), along with hands-on expertise in fine-tuning foundational models using AWS services like Amazon SageMaker and AWS Bedrock. The role requires a deep understanding of AI/ML workflows and the ability to implement advanced prompt optimization methods to enhance model performance.

Personal Characteristics

• Strong portfolio and excellent attitude.
• Must be self-confident to work in a Team and to handle the responsibilities individually as well
• Should be a good listener/ Can articulate well / Good Communication Skills Ability to work with teams across organizational boundaries, different cultures and different time zones in a virtual environment
• Delivery oriented and able to work under strict deadlines.

•  Design and implement advanced prompt engineering strategies, including ToT, CoT, and other optimization methods. 
• Fine-tune pre-trained foundational models using AWS services such as Amazon SageMaker and AWS Bedrock. 
• Develop and optimize ML workflows for efficient training, inference, and deployment. 
• Leverage JumpCloud for identity and security management within the ML environment. 
• Collaborate with data scientists, engineers, and business stakeholders to integrate AI-driven solutions. 
• Monitor model performance and continuously refine prompts and training methodologies for better accuracy. 
• Stay updated with the latest research and trends in prompt engineering and ML fine-tuning.