Overview
On Site
$50 - $60
Contract - W2
Contract - 12 Month(s)
Skills
generative AI
Job Details
Responsibilities:
- Develop and implement core components of generative AI solutions including RAG pipelines and context engineering features within the established architecture; drive quality into prompt engineering and optimization for business use cases
- Collaborate closely with product managers, senior data scientists, and AI engineers to translate feature requirements into production-ready code and contribute to the team's technical objectives
- Focus on continuous innovation by assisting in prototyping modern AI agent and orchestration patterns using frameworks like LangChain/LangGraph
- Drive the delivery of robust data science features by taking ownership of specific modules from development and experimentation through to deployment
- Engage in agile ceremonies and contribute to the team's collective knowledge of generative AI, audit methodologies, and best practices
- Enhance AI and RAG evaluation frameworks using tools like LangSmith; ensure solutions meet KPMG's standards for quality
- Provide technical leadership and mentorship to junior data scientists; guide hands-on work in context engineering, model tuning, and advanced data analysis
- Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment
Qualifications:
- 8+ years of recent experience in data science, machine learning engineering, or a similar role with a focus on building and deploying AI models
- Master's degree from an accredited college or university in computer science, data science, statistics, or a related technical field is preferred; minimum of a bachelor's degree is required
- Experienced in working with LLMs, AI frameworks like LangChain or Semantic Kernel, and building AI-powered applications
- Strong programming skills in Python and its data science libraries; experience with Azure, Databricks, or Microsoft Fabric is a significant plus
- Proficient with SDLC tools and methodologies including Git, Azure DevOps, and working within an agile framework
- Excellent problem-solving skills; able to communicate technical details effectively within a collaborative team environment
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