Salesforce CPQ Architect & Machine Learning Engineer - Fraud Detection
Innovim Technology Solutions
Position: Salesforce CPQ Architect
Location: Milwaukee, WI (Onsite)
Summary:
- A hands-on Salesforce CPQ Architect to lead the design and delivery of complex Quote-to-Cash solutions for an enterprise client.
- You will own the end-to-end CPQ architecture - from product catalog and pricing strategy through quoting, approvals, contracts, and downstream billing/ERP integration - while working onsite alongside client business and IT stakeholders.
Description:
- Bachelor's degree or Master's Degree in Computer science, or a related field, with minimum 12+ Years of relevant experience.
- 5+ years of hands-on Salesforce CPQ implementation experience, with 2+ full-lifecycle enterprise deployments in an architect role
- Deep expertise in product bundling, price rules, quote calculator plugins (QCP), advanced approvals, and contract/amendment/renewal flows
- Strong understanding of Quote-to-Cash and Lead-to-Order processes, including billing and revenue recognition touchpoints
- Experience integrating Salesforce with ERP systems (SAP, Oracle, NetSuite) via middleware
- Proficiency with Sales Cloud architecture, Flow, Apex (read/review level), and data modeling
- Salesforce CPQ Specialist certification required; Application Architect or System Architect strongly preferred
- Excellent client-facing communication skills and proven ability to operate independently onsite
- Exposure to Salesforce Revenue Cloud / Revenue Lifecycle Management (RLM) and migration considerations from legacy CPQ
- Experience with Conga or DocuSign CLM, Salesforce Billing, or subscription/recurring-revenue models (e.g., monitored services, SaaS-attached hardware)
- Industry experience in building technologies, HVAC, fire & security, industrial equipment, or discrete manufacturing - including engineered-to-order and configure-to-order product models
- Familiarity with channel/dealer quoting models and field sales organizations
- Prior consulting background (Big 4 or boutique SI)
Position: Machine Learning Engineer - Fraud Detection
Location: Dallas, TX (Hybrid)
Description:
- Bachelor's degree or Master's Degree in Computer science, or a related field, with minimum 12+ Years of relevant experience.
Role Summary
- We are looking for a Machine Learning Engineer to build and support production-grade fraud detection solutions.
- The role focuses on real-time inference, feature engineering, APIs, graph-based fraud detection, and production deployment support.
Key Skills
- Good Experience in Machine Learning Engineering and Real-Time Inference
- Strong in Python, APIs, and Microservices
- Good Experience in GCP and Databricks
- Strong in Neo4j / Graph Databases and Feature Stores
- Data Pipelines and Feature Engineering
- MLOps, Monitoring, and Production Support
- Agentic AI Architecture (good to have)
Required Qualifications
- Hands-on experience in Python and ML model deployment.
- Experience with APIs, microservices, and production ML systems .
- Knowledge of data pipelines, data engineering, and feature stores.
- Exposure to GCP, Databricks, Data Lake, or Data Warehouse platforms.
- Basic understanding of MLOps, monitoring, and release support .
- Good communication and problem-solving skills.
Nice to Have
- Fraud detection, risk analytics, or scoring model experience.
- Experience with Neo4j or graph-based ML solutions.
- Understanding of Agentic AI architecture.
Vacancy posted 3 days ago
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