JOBSEARCHER

Machine Learning Engineer 5 - Decisioning & Optimization

ARCHIVED

We can't find an active application page for this role right now. It may reopen or be listed elsewhere. Use Next Steps to search for an active apply link and similar live jobs.

For our client, we are seeking a Machine Learning Engineer 5 - Decisioning & Optimization to join the team of a leader in the Hospitality & Recreation space. This role will lead technical initiatives focused on scalable systems, platform reliability, and meaningful business transformation. You will work across engineering, product, operations, and business stakeholders to translate complex requirements into practical technology solutions. The position offers the opportunity to influence architecture, execution quality, and the technology capabilities that enable long-term growth within a healthcare environment.Location: Los Angeles, CA - US based candidates only, no visa sponsorship availableCompensation: $466,000 – $750,000 annuallyResponsibilities Build and manage ML model serving infrastructure for real-time ad decisioning Scale inference operations to support multiple models per ad request at high QPS Design and optimize feature serving paths for rapid data access Productionize scoring and ranking models for ad selection and auction integration Implement performance monitoring for production ML models to ensure reliability Collaborate with Data Science and Platform teams for effective outcomes Create simulation infrastructure to test models against production trafficQualifications 7+ years of software engineering experience; 3+ years focused on ML infrastructure in an ad or real-time decisioning context Experience building real-time model serving systems that achieve sub-20ms latency at high QPS Proficiency in Java, Python, or Scala with knowledge of multi-threading and performance optimization Hands-on experience with ML serving frameworks and deployment constraints Experience with real-time feature engineering and ensuring online/offline consistency Strong understanding of model monitoring techniques in production environments Ability to shift from ML research outputs to production-ready servicesBenefits Comprehensive health plans and mental health support 401(k) retirement plan with employer match and stock option program Disability programs and flexible spending accounts Family-forming benefits and paid leave of absence programs Generous paid time off: 35 days annually for hourly employees, flexible time off for salaried employeesOur client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.