AI-ML Solution Architect - Part time

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 6 Month(s)

Skills

AI-ML Solution
Domain knowledge in transportation/transit and healthcare

Job Details

Job title: AI-ML Solution Architect Location: New Jersey, USA Hybrid/Remote

About the Role

We're seeking a strategic AI-ML Solution Architect with a strong background in transportation and healthcare to lead AI platform architecture, advisory, and implementation initiatives. The ideal candidate brings a deep understanding of ML, LLMs, cloud integration, and business alignment to drive enterprise-scale AI solutions.

Key Responsibilities

  • Provide strategic and advisory leadership on AI/ML initiatives across transportation and healthcare domains.
  • Perform gap analysis, define high-impact AI use cases, and guide solution development to address them.
  • Architect scalable AI platforms leveraging ML, Deep Learning, and LLMs across cloud ecosystems (Google Cloud Platform, Azure, AWS).
  • Collaborate closely with business teams to gather requirements and translate them into AI-driven outcomes.
  • Integrate and optimize LLMs from major AI platforms, including OpenAI (ChatGPT), Google Gemini, Groq, and Azure OpenAI, tailored to enterprise use cases.
  • Lead infrastructure design, cloud service selection, data pipeline creation, and model deployment.
  • Define and enforce AI/ML architecture standards, data governance, and security best practices.
  • Evaluate emerging AI tools and platforms for enterprise fit and strategic value.
  • Communicate architectural decisions to technical and executive stakeholders.
  • Mentor development teams and optimize performance across cross-functional environments.

Required Experience & Skills

  • 15+ years in IT, including 5+ years in AI/ML solution architecture.
  • Proven ability to engage with business teams, define AI opportunities, and deliver solutions.
  • Strong domain knowledge in transportation/transit and healthcare.
  • Expertise in ML/DL frameworks (TensorFlow, PyTorch, Scikit-Learn) and LLMs integration.
  • Hands-on experience with cloud AI platforms: Google Cloud Platform, Azure, AWS.
  • Skilled in MLOps, data engineering, containerization (Docker, Kubernetes), and CI/CD pipelines.
  • Familiarity with model lifecycle management, governance, and compliance.
  • Excellent communication and leadership skills to influence across technical and executive levels.

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