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AI MODELER/ENGINEER

Expert In Recruitment Solutions

Job Description

Job Description

AI MODELER/ENGINEER:
assessment required
hybrid malvern, pa
Job Description
Technical Stack & Requirements:

  • AI/ML Stack: Amazon SageMaker, AWS Bedrock.
  • Design Focus: Vector databases, knowledge graphs, and semantic layers.
  • Databricks: Experience with Databricks and Databricks Genie is highly desirable.
  • Core Mandate: Define the standards for "AI-ready" data curation and direct the integration of AI methodologies into existing Service Experience and Financials business logic.
Qualifications:
  • 6-8 years of experience.
  • Strong background in AI/ML design and implementation.
  • Ability to architect semantic layers and knowledge graphs.
  • Experience with GitHub Actions for managing codebases.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
  • 8 years of software engineering experience.
  • 3 years of hands-on AI/ML engineering experience.
  • Advanced Python programming skills.
  • Strong experience building production-grade AI applications.
  • Experience with Generative AI and Large Language Models.
  • Experience designing Retrieval-Augmented Generation (RAG) architectures.
  • Knowledge of vector databases and embedding models.
  • Experience deploying AI solutions on AWS cloud platforms.
  • Experience with CI/CD pipelines and DevOps practices.
  • Strong understanding of distributed systems and scalable backend architectures.
  • Excellent communication and stakeholder management skills.
Preferred Qualifications
  • Experience with Agentic AI frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel).
  • Experience with AWS Bedrock, Amazon SageMaker, Azure OpenAI, or Vertex AI.
  • Experience implementing Responsible AI frameworks.
  • Financial services, fintech, or investment management domain experience.
  • Experience building recommendation engines, intelligent assistants, or AI copilots.
  • Knowledge of Kubernetes, Docker, and cloud-native microservices.
  • AWS AI/ML certifications or equivalent.
Vacancy posted 4 days ago
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