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AI/ML Architect (Generative AI & LLMs)

Hybrid in Grand Rapids, MI, US • Posted 1 day ago • Updated 1 day ago

Contract W2

No Travel Required

Hybrid

Depends on Experience

Fitment

Dice Job Match Score™

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Job Details

Skills

AI/ML
Artificial Intelligence
Machine Learning (ML)
Generative Artificial Intelligence (AI)
Architect
Machine Learning Operations (ML Ops)
Data Science
Amazon Web Services
Continuous Integration
Continuous Delivery
Microsoft Azure
Microservices
Software Engineering
PyTorch
Python
Google Cloud Platform
Extract, Transform, Load
DevOps
Deep Learning

Summary

Note: This is contract on W2 Position.

Job Description:

We are seeking an experienced AI/ML Architect to lead the design and delivery of scalable AI solutions across the organization. The role focuses on building and governing architecture for Generative AI, LLMs, and traditional machine learning systems, while defining best practices for MLOps, data pipelines, and AI system design.

Required Qualifications

Total 15+ years in software engineering / data science, with 5–8+ years in AI/ML architecture roles
Strong experience in AI/ML architecture and system design
Strong experience with RAG (Retrieval-Augmented Generation)
Expertise in machine learning, deep learning, and NLP
Hands-on experience with LLMs / Generative AI (e.g., GPT, Llama)
Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn
Experience with cloud platforms (AWS, Azure, or Google Cloud Platform AI services)
Strong knowledge of data engineering (ETL pipelines, data lakes, streaming)
Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI)
Understanding of APIs, microservices, and distributed systems
Knowledge of vector databases
Experience with DevOps / CI-CD pipelines for ML
Exposure to AI governance and compliance

Key Responsibilities

Define and drive the AI/ML architecture strategy across the organization
Design end-to-end AI solutions, including GenAI, LLMs, and traditional ML models
Lead architecture design for scalable data pipelines and real-time/streaming systems
Establish and implement MLOps practices for model versioning, deployment, and monitoring
Collaborate with AI and Data teams to define best practices in AI system design
Evaluate emerging AI technologies and define adoption strategies

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91099677
Position Id: 8952598
Posted 1 day ago

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