AI/ML Engineer
Simarn Solutions · simarn.com
MinneapolisSenior5–7 yrsContract
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The job in short
AI/ML engineering.
AWSAzurePower BISalesforceLLMsTransformersRAGCompliance
Details
- Found
- 21 d ago · posted 2026-10-04
- Location as listed
- Minneapolis, Minnesota, United States
- Role
- Machine Learning / AI Engineer
- Source
- The company’s own careers site
Full description
AI/ML Engineer
Location: Minneapolis, MN
Job Type (C2C): C2C
Job Mode: Remote
Pay Rate: $65/hr
Industry: Information Technology / AI & CRM Integration
End Date: 01-Dec-2026
Job Description
We are seeking an AI/ML Engineer with strong expertise in Salesforce enhancements, real-time model deployment, and intelligent automation. The role involves developing AI/ML models, integrating them into Salesforce CRM, enhancing workflows with native and external AI technologies, and building RAG pipelines for contextual insights. The engineer will also extend Salesforce functionality using Apex, LWC, and related tools to support advanced AI-driven capabilities.
Responsibilities
• Design, develop, test, and deploy Salesforce solutions based on business needs.
• Build and deploy AI/ML models for automation and real-time decision-making.
• Integrate AI/ML solutions with Salesforce CRM using Einstein GPT and external ML services.
• Enhance Salesforce applications with AI-driven recommendations, forecasting, and workflow intelligence.
• Develop RAG pipelines using vector databases and LLMs to improve contextual understanding.
• Extend Salesforce functionality using Apex classes, triggers, LWC, Aura, Visualforce, and APIs.
Required Qualifications
• Bachelors degree in Computer Science, Information Systems, Statistics, or related field.
• 5-7 years of experience in Power BI development and implementation.
• Strong experience building and deploying AI/ML models.
• Hands-on experience integrating AI/ML systems with Salesforce CRM.
• Knowledge of LLMs, transformers, and RAG pipelines.
• Experience developing AI-based automation (Einstein Bots, custom bots).
• CI/CD experience with Git.
• Cloud experience with Azure/AWS ML services.
• Strong understanding of data privacy, security, scalability, and compliance for production ML models.
• Ability to collaborate with engineering, data, and product teams.
• Experience monitoring model accuracy and implementing continuous feedback loops.
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