Job Description
About Our Client The organization operates decentralized online marketplaces that connect consumers who research and compare products with brands. It manages one of the nation’s largest media networks through virtual and private-label marketplaces. Using segmentation and AI-driven matching technologies, the program helps consumers find solutions more efficiently while enabling brands to target in-market prospects accurately and pay based on performance results. The company’s matching decision engines and optimization algorithms are developed from over 20 years and billions of dollars of online media experience, focusing on measurable digital media outcomes and performance marketing. About the Opportunity The Senior Machine Learning Engineer - Ranking role focuses on shaping how users discover and interact with the marketplace by advancing algorithms for ordering, prioritization, and personalization. Ranking is critical to helping users find ads while balancing user satisfaction, business objectives, and system health. This position drives improvements in ranking systems through rigorous measurement and experimentation, contributing directly to the effectiveness and reliability of the platform’s recommendation capabilities. Responsibilities Design and enhance ranking systems with clear metrics and validated improvements. Develop evaluation methods to support evidence-based decision-making. Build and maintain high-value features and signals with robust pipelines and monitoring. Manage model stability through uncertainty-aware decisions, drift handling, and calibration. Collaborate with Engineering, Product, Business, and Analytics teams to deliver end-to-end solutions. Requirements Advanced degree (MS/PhD) in Computer Science, Statistics, or related field with 3+ years post-PhD or 5+ years of industry experience. Strong expertise in applied machine learning, statistics, and optimization with proven impact in ranking or recommendation systems. Proficiency in Python and software engineering practices including testing and CI/CD. Experience with large-scale datasets, distributed systems, and latency-sensitive production ML environments. Effective communication, cross-functional collaboration, and a strong ownership mindset. Preferred Qualifications Experience delivering production-grade ranking systems with measurable business results. Background building feature pipelines, feature stores, and ML system observability. Expertise in experimentation and metric design, including large-scale A/B testing and variance reduction. Knowledge of monitoring, calibration, concept drift detection, and adaptive or online learning. Proficiency in SQL preferred. Familiarity with Linear Algebra and Combinatorial Optimization. Experience in scalable software design and development. Exposure to multimodal signals (text, image, metadata) is a plus. Compensation & Benefits Compensation Expected Salary Range: $140,000 USD to $170,000 USD annually. This range is an estimate and may vary based on the organization’s compensation practices and the candidate’s geographic location. The position is eligible for performance bonuses or commissions and equity in the form of restricted stock units (RSUs). Benefits & Perks Participation in the organization’s standard employee benefits programs, including health care, retirement, paid time off, and other tax-reportable benefits. Equal Opportunity Statement Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin. About RemoteHunter RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.