13 days ago

AI Architect

Acnovate Corporation

Hybrid
Contractor
$150,000
Hybrid

Job Overview

Job TitleAI Architect
Job TypeContractor
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$150,000
LocationHybrid

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Job Description

About the AI Architect Role

The AI Architect at Acnovate Corporation is responsible for designing and delivering production AI solutions. This role requires 9+ years of experience in software, data, or AI engineering, with at least 5 years of specialization in AI/ML architecture.

Required Qualifications

  • 9+ years of experience in software, data, or AI engineering
  • 5+ years in AI/ML architecture roles
  • Proven experience in production AI solutions in retail, e-commerce, or supply chain
  • Hands-on expertise in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn
  • Experience with modern data architectures, lakehouse, streaming, and batch pipelines
  • Knowledge of modern data platforms like Databricks and Snowflake
  • Familiarity with cloud platforms and managed AI/ML services
  • Experience with MLOps practices, including model lifecycle management, monitoring, and CI/CD
  • Solid understanding of LLMs, Generative AI patterns, and AI system integration
  • Excellent communication skills to articulate complex architectures

Preferred Qualifications

  • Deep experience in retail or consumer-facing industries
  • Experience scaling enterprise AI platforms or AI Centers of Excellence

Key skills/competency

  • AI
  • ML
  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Data Pipelines
  • Cloud
  • MLOps
  • LLMs

Tags:

AI Architect
AI
ML
architecture
cloud
data
retail
ecommerce
supply chain
MLOps
Python
PyTorch
TensorFlow
scikit-learn
Databricks
Snowflake

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How to Get Hired at Acnovate Corporation

  • Research Acnovate Corporation's culture: Understand their mission and industry focus.
  • Customize your resume: Highlight AI and ML architecture experience.
  • Emphasize technical skills: Clearly showcase Python, PyTorch, and TensorFlow.
  • Prepare for interviews: Be ready to discuss production AI implementations.

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