Job description
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.
Key Responsibilities
- 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.