Negotiable
Outside
Remote
USA
Summary: The role of AI/ML Expert Consultant involves leveraging expertise in Amazon Q Business and related AWS AI services to enhance data retrieval and optimization processes. The consultant will be responsible for teaching and upskilling a team in machine learning and generative AI techniques. This position requires strong communication skills and a solid background in AI technologies. The role is remote and expected to last for over six months.
Key Responsibilities:
- Design and implement documentation ingestion workflows using Amazon Q Business and related AWS AI services
- Develop and maintain data preprocessing pipelines with focus on data quality improvement
- Lead initiatives to standardize and enhance documentation quality
- Assess response quality through ground truth analysis to optimize for business use cases
- Establish and monitor content quality metrics
- Collaborate with content owners to improve documentation structure and metadata
Key Skills:
- Experience with AWS AI services, including Amazon Q Business and Amazon Bedrock
- Knowledge of effective prompt engineering and RAG implementation
- Understanding of content chunking, vectorization, and metadata strategies
- Proficiency in Python programming language
- Experience in data quality assessment and content standardization methodologies
- Experience working with large language models (LLMs)
- Advanced planning, organizational, problem-solving, analytical, decision-making and communication skills required
- Must be able to maintain a high degree of accuracy and confidentiality
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Hi ,
My name is Tanya. I just received details on a great job that I believe you would be a great fit for. Please take a look below and share your interest.
Title- AI/ML expert consultant
Location=- Remote
Duration- 6+ months
Interview- video
- This person needs to have enough experience to teach an entire team how to do the work
This group is in the Data and Analytics area. They want to build up the AI world when it comes to the retrieval of data to optimize it. They are using ML / Gen AI to do this.
Purpose of the team:
- Use Gen AI to retrieve the appropriate data from the sources. Then scale and optimize the data.
- They are already working with an established code base.
Must have skills:
- They are building this on Amazon Q Business. Thid has only been out for 1 years. They just need someone that has worked with it.
- If they have not worked with Q Business, to be considered for this role, they would have to have a strong background with Amazon Bedrock and RAG (Retrieval Augmentation Generation) Implementations experience.
- They want someone to help upscale their team as they learn ML / Gen AI and the Amazon Q Business suite of services.
- Strong communication skills are important as they teach the team.
Qualifications:
* Experience with AWS AI services, including Amazon Q Business and Amazon Bedrock
* Knowledge of effective prompt engineering and RAG implementation
* Understanding of content chunking, vectorization, and metadata strategies
* Proficiency in Python programming language
* Experience in data quality assessment and content standardization methodologies
* Experience working with large language models (LLMs)
* Advanced planning, organizational, problem-solving, analytical, decision-making and communication skills required
* Must be able to maintain a high degree of accuracy and confidentiality
Responsibilities:
* Design and implement documentation ingestion workflows using Amazon Q Business and related AWS AI services
* Develop and maintain data preprocessing pipelines with focus on data quality improvement
* Lead initiatives to standardize and enhance documentation quality
* Assess response quality through ground truth analysis to optimize for business use cases
* Establish and monitor content quality metrics
* Collaborate with content owners to improve documentation structure and metadata