Principal ML Engineer
$300,000–$375,000 year
RemoteUnited States
Job Summary
Lead the design, build, and evolution of production ML algorithms and systems driving ranking, rewards, ROAS/LTV prediction, offer optimization, and experimentation for a platform serving 120M+ users. Personally drive critical implementations, architect scalable offline/online systems, and establish robust experimentation frameworks connecting model performance to business outcomes. Make key decisions on MLOps, observability, and serving patterns while partnering with Data Engineering, BI, and Product teams. Mentor engineers through direct contribution, code reviews, and raising technical standards. Operate within a fast-moving AdTech environment with 50M daily events and 100TB data lake.
Required Qualifications
- 8+ years of experience in software engineering, machine learning engineering, MLOps, or related technical fields
- 5+ years building, deploying, and supporting production ML systems at scale
- Strong experience in AdTech, MarTech, Growth, Performance Marketing, or adjacent domains
- Strong hands-on background in: ranking recommendation rewards / incentives ROAS / LTV prediction personalization / optimization systems
- Proven experience designing, shipping, and operating production ML systems end to end
- Strong understanding of: offline / online ML architecture feature engineering and feature platforms model serving patterns experimentation frameworks for ML systems
- A/B testing and measurement design
- MLOps, retraining, monitoring, and governance
- Experience partnering closely with Data Engineering / BI / Analytics teams to create clean, scalable, and trustworthy data foundations for ML
- Strong system design skills with sound judgment across performance, reliability, scalability, and cost
- Ability to guide teams toward an AI-first way of working, while maintaining strong validation and engineering discipline
- Strong technical leadership and mentoring capability, with the ability to influence across teams without direct authority
- Comfort operating in ambiguity and still driving systems into production
Desired Qualifications
- Experience with counterfactual reasoning, causal inference, or uplift modeling
- 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
- Master's degree or PhD in AI, Machine Learning, or a quantitative field
- Familiarity with modern AI-assisted / AI-first development practices across engineering and data science teams
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