Machine Learning Architect

Role description

Job Title: ML Architect

Location: Irving, TX, USA (Work from Office)

Industry/Field: Telecom Media

Experience: 10-15 years

Company: Tredence

About Us:

Tredence differentiates itself from other analytics services firms by enabling last mile adoption of insights. We drive true business impact by uniting our strengths in business analytics, data science, and software engineering. We help our clients deliver on the artificial intelligence imperative, in a practical and demystified way. To know more about us, visit: www.tredence.com

In this role, you will serve as both the technical architect and a hands-on implementation lead. You will drive discussions with core engineering teams, collaborate with key external partners (Google, GrowthLoop, and MetaRouter), and build real-time agentic AI workflows using Google Reasoning Engine, GCP Cloud Spanner, GCP BigQuery, and modern martech orchestration engines.

Responsibilities

• Lead technical discussions, design reviews, and roadmap alignment with core engineering implementation groups, enterprise stakeholders, and technology partners (Google, GrowthLoop, MetaRouter).
• Hands-on Solutioning & Architecture [strong data-path-to-node="9,1,0" data-index-in-node="0"] : Architect and co-implement real-time and batch pipelines across Google Cloud Platform (GCP) and Google Marketing Platform (GMP).
• Agentic AI & Decisioning Engine Deployment: Lead the integration of Google Reasoning Engine for dynamic offer prioritization, Next Best Offer (NBO), and personalized campaign content generation.
• Data Integration & Ingestion: Oversee client-side real-time tag routing via MetaRouter, real-time event streaming via GCP Pub/Sub, and low-latency profile storage via GCP Cloud Spanner.
• Audience & Journey Orchestration: Work closely with GrowthLoop for audience membership/segmentation and GrowthLoop Orchestration (Journey Engine) to execute business rules and instant triggers.
• Cross-Functional Collaboration: Partner with cross functional technology teams across different channels like POS, Digital & Assisted.

Qualifications & Skills

• Experience: 7+ years in MarTech/AdTech architecture, Cloud Data Engineering, or AI Solution Architecture.
• GCP Expertise: Deep experience across Google Cloud ecosystem, including Cloud Spanner, BigQuery, Pub/Sub, and Vertex AI / Google Reasoning Engine.
• Desired Technologies: Hands-on experience or familiarity with MetaRouter, GrowthLoop, Optimizely, and Adobe ecosystem tooling (AEM/AEP etc).
• AI & Agentic Workflows: Proven experience designing real-time recommendation/decision engines using LLMs, Agentic AI, or ML models.
• Data Engineering & Streaming: Deep knowledge of real-time streaming (Pub/Sub, websockets, low-latency key-value/document stores) and batch ETL/ELT pipelines.
• Leadership: Exceptional communication skills with a proven track record of bridging the gap between high-level business requirements and hands-on technical execution.