Job Description: Strategic Imperative: The Principal ML Engineer will lead the architecture, design, and evolution of machine learning across our Performance Marketing domain. This role is for a senior technical leader with deep experience in AdTech / MarTech, especially in ranking, rewards, ROAS / LTV modeling, and optimization systems. The role will define the ML vision for the domain, guide model and data architecture, make key decisions on MLOps, modelling and experimentation, tooling, and scalable system design, and mentor a growing team of engineers and data scientists. Just as importantly, you will help build an AI-first engineering mindset across the ML organization, using AI where it meaningfully improves speed, quality, insight generation, and decision-making. Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today! Primary Objectives: - Advanced Level ML Architecture & Technical Direction - End-to-End Machine Learning Systems Delivery - Productionization, Reliability & Lifecycle Management - Advanced Experimentation, Monitoring & Model Performance Optimization - Scalable AI Platform, Feature & Inference Enablement - Cross-Functional Technical Leadership & Business Partnership - Engineering Standards, Mentorship & AI Capability Enablement Qualifications - To perform this job successfully, an individual must be able to perform each job duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Detailed Job Duties: (typical monthly, weekly, daily tasks which support the primary objectives) - Define the machine learning strategy and technical vision for Performance Marketing - Lead the development of sophisticated models, from selecting loss functions and architectures to fine-tuning hyperparameters and managing deployments. - Build "Version 0" of critical systems, writing production-quality code to prove out new modeling approaches before scaling them across the team. - Architect and evolve ML systems across areas such as: - ranking and recommendation - rewards optimization - ROAS / LTV prediction - campaign and offer optimization - experimentation and decisioning systems - Design scalable ML architectures across offline training, online inference, feature generation, feedback loops, and model monitoring - Partner closely with the Data team to define the right data models, data contracts, feature pipelines, training datasets, and measurement foundations needed for reliable ML systems - Establish the right experimentation framework for ML models, including offline evaluation, online testing, A/B experimentation, KPI design, and post-launch performance measurement - Lead by example through active code contributions and deep-dive PR reviews, ensuring high standards for model performance and system reliability. - Make key decisions on MLOps, tooling, infrastructure, model serving, observability, and platform architecture - Drive an AI-first mindset within the ML organization by using AI to accelerate research, prototyping, feature engineering, experimentation analysis, documentation, model debugging, and developer productivity where it makes sense - Guide the team on how to build systems that are scalable, reliable, cost-aware, and production-ready - Partner with Product, Engineering, Analytics, and business teams to translate commercial goals into ML roadmaps - Mentor ML engineers and data scientists, helping raise the bar on model quality, engineering rigor, and technical judgment - Set best practices for model validation, monitoring, retraining, drift detection, explainability, and governance The MUST Haves: (ex: job cannot be done without these skills, education, experience, certifications, licenses) - Bachelor’s degree in a relevant technical field, or equivalent practical experience. - Eight or more (8+) years of experience in software engineering, machine learning engineering, MLOps, or a related field. - Five or more (5+) years of experience building, deploying, and supporting production machine learning systems at scale. - Deep experience in Machine Learning engineering in AdTech, MarTech, Growth, Performance Marketing, or adjacent domains - Strong background in: - Ranking - Recommendation - rewards / incentives - ROAS / LTV prediction - personalization / optimization systems - Proven experience designing and shipping production ML systems at scale - Strong understanding of: - feature engineering and feature stores - offline / online ML architecture - model serving patterns - experimentation frameworks for ML systems - A/B testing and measurement design - MLOps, monitoring, retraining, and model governance - Experience with Counterfactual Reasoning, Causal Inference, or Uplift Modeling. - Experience working closely with Data Engineering / BI / Analytics teams to ensure clean, scalable, and trustworthy data foundations for ML - Strong system design skills with ability to make the right tradeoffs across performance, reliability, scalability, and cost - Ability to guide teams toward an AI-first way of working, using AI as a force multiplier for model development, experimentation, and engineering productivity - Strong judgment around where AI adds leverage and where human review, rigor, and validation remain essential - Ability to lead technically across teams and influence architecture decisions without direct authority - Strong mentoring and leadership skills; able to guide junior engineers and shape a strong ML engineering culture The Nice to Haves: (ex: preferred additional skills, education, experience, certifications, licenses) - Master’s degree or PhD in AI, Machine Learning, or a quantitative field. - Experience in rewards, offer ecosystems, customer value optimization, or monetization platforms - Experience with streaming or near-real-time decisioning systems - Experience building ML platforms or shared experimentation infrastructure - Familiarity with modern AI-assisted / AI-first development practices across engineering and data science teams Pay Transparency: The anticipated base salary range for this position is $300,000 to $375,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Prodege Benefits: Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year. Employees receive an option to purchase shares of Company stock commensurate with their position, which vests over four years. Equal Employment Opportunity Statement At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply. FCIHO Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.