Remote!! AI/ML Expert with Amazon Q Business

Remote!! AI/ML Expert with Amazon Q Business

Posted 6 days ago by 1755842560

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

Detailed Description From Employer:

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:

  1. Use Gen AI to retrieve the appropriate data from the sources. Then scale and optimize the data.
  2. They are already working with an established code base.


Must have skills:

  1. 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.
  2. 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.
  3. They want someone to help upscale their team as they learn ML / Gen AI and the Amazon Q Business suite of services.
  4. 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