AI/ML Engineer

Overview

Remote
Depends on Experience
Contract - W2

Skills

Amazon Web Services
Apex
Artificial Intelligence
Cloud Computing
Collaboration
Continuous Delivery
Continuous Improvement
Continuous Integration
Decision-making
Forecasting
Generative Artificial Intelligence (AI)
Git
Large Language Models (LLMs)
Machine Learning (ML)
Management
Microsoft Azure
Microsoft Power BI
Oracle Application Express
Privacy
Python
Real-time
Regulatory Compliance
Sales
Salesforce.com
Scalability
User Experience
Vector Databases
Visualforce
Web Services
Workflow

Job Details

Job Title: AI/ML Engineer

Location: Minneapolis, MN(Remote)

Rate: $52/hr on W2 or $57/hr on 1099

Job Description:

1. Design, develop, test, document, and deploy Salesforce solutions based on business needs.

2. Develop and deploy AI/ML models for real-time decision-making and automation.

3. Integrate AI/ML solutions into Salesforce CRM to enable intelligent data retrieval, personalized recommendations, workflow automation, forecasting, scoring, and opportunity insights.

4. Enhance Salesforce applications with advanced AI features using both native (Einstein/Einstein GPT) and external technologies (Python-based models or Azure/AWS ML services).

5. Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and Large Language Models (LLMs) for improved contextual understanding within Salesforce workflows.

6. Extend platform functionality using Apex (Triggers/Classes), LWC, Aura Framework, Visualforce Pages, Apex APIs and web services.

MUST HAVE SKILLS

1. Bachelor's degree in Computer Science, Information Systems, Statistics, or a comparable discipline is required, with prior experience in data analysis or a related field being advantageous

2. 5-7 years of experience in Power BI development and implementation

3. AI/ML Expertise: Building and deploying models for real-time decision-making and automation.

4. Integration Skills: AI/ML integration with Salesforce CRM (Einstein/Einstein GPT and external technologies like Python-based models or Azure/AWS ML services).

5. Generative AI Knowledge: Familiarity with transformers, LLMs, and Retrieval-Augmented Generation (RAG) pipelines using vector databases.

6. Automation Development: Creating AI-powered automation solutions, including Einstein Bots and custom bots for sales/service workflows.

7. CI/CD Proficiency: Managing deployment processes using Git.

8. Cloud Platforms: Experience with Azure/AWS ML services and enterprise-grade integrations.

9. Security & Compliance: Ensuring data privacy, scalability, and reliability of AI models in production.

10. Collaboration: Ability to work with product managers, engineers, and data teams for AI-driven enhancements.

11. Continuous Improvement: Monitoring model accuracy and implementing feedback loops for better user experience.

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.

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