Senior Machine Learning Engineer - Ranking

Quinstreet; United States; Remote; USD 140,000 - 170,000; Full time

Benefits offered by this job

Performance bonus

Equity in RSUs

Health insurance

Retirement benefits

Paid time off

Job summary

QuinStreet seeks a senior researcher to advance ranking systems and personalization across its digital marketplaces. You will design experiments, build signals from text/image/metadata, and optimize models with measurable business impact.

Work with Engineering, Product and Analytics to deploy end-to-end ML solutions that balance user satisfaction, revenue goals, and system health. This role is remote in the United States.

Qualifications

• Advanced degree (MS/PhD) in CS, Statistics, or related field.
• 3+ years post-PhD or 5+ years industry experience in ML/ranking.
• Strong foundations in applied ML, statistics, and optimization with impact on ranking/recommendations.
• Proficiency in Python and software engineering practices (testing, CI/CD).
• Experience with large-scale datasets, distributed systems, and latency-sensitive production ML.

Responsibilities

• Design and improve ranking systems through measurement and experimentation; translate goals into metrics and gains.
• Advance evaluation practices (offline & online alignment) and help teams make evidence-based decisions.
• Build high-value signals and features with offline/online pipelines and monitoring.
• Make uncertainty-aware decisions; handle drift and calibration for stable models.
• Partner with Engineering, Product, Business and Analytics to ship resilient solutions end-to-end.

Skills

Applied ML

Statistics

Optimization

Python

Distributed systems

A/B testing

Communication

Education

MS/PhD in CS or Statistics

Tools

SQL

Job description

Powering Performance Marketplaces in Digital Media

QuinStreet is a pioneer in powering decentralized onlinemarketplaces that match searchers and “research and compare” consumers with brands. We run these virtual- and private-label marketplaces in one of the nation’s largest media networks.

Our industry leading segmentation and AI-drivenmatching technologies help consumers find better solutions and brands faster.They allow brands to target and reach in-market customer prospects with pinpoint segment-by-segment accuracy, and to pay only for performance results.

Our campaign-results-driven matching decision engines and optimization algorithms are built from over 20 years and billions of dollars of online media experience.

We believe in:

• The direct measurability of digital media.
• Performance marketing. (We pioneered it.)
• The advantages of technology.

We bring all this together to deliver truly great results for consumers and brands in the world’s biggest channel.

Job Category

Join us to shape how users discover and interact with our marketplace. You’ll advance algorithms for ordering, prioritization, and personalization. Ranking is a core component which helps users discover ads, balance user satisfaction, business goals, and system health.

Responsibilities

• Design and improve ranking systems through rigorous measurement and experimentation; translate broad goals into clear metrics and deliver steady, validated gains.
• Advance evaluation practices (clean test design, offline & online alignment) and help teams make evidence-based decisions.
• Build high-value signals and features with reliable offline/online pipelines and robust monitoring. Incorporate content understanding signals such as text/image/metadata.
• Make uncertainty-aware decisions; handle drift and calibration so models remain stable and trustworthy over time.
• Partner with Engineering, Product, Business and Analytics to ship resilient solutions end-to-end.

Requirements

• Advanced degree (MS/PhD) in CS, Statistics, or related field, with 3+ years post-PhD or 5+ years industry experience.
• Strong foundations in applied ML, statistics, and optimization with demonstrated impact in ranking/recommendations.
• Proficiency in Python and solid software engineering practices (testing, CI/CD).
• Experience working with large-scale datasets, distributed systems, and latency-sensitive production ML.
• Clear communication, cross-functional collaboration, and an ownership mindset.

Preferred

• Demonstrated success in delivering production-grade ranking systems with measurable business impact.
• Track record building feature/signals pipelines, feature stores, and observability for ML systems.
• Depth in experimentation and metrics design, including large-scale A/B testing and variance reduction.
• Familiarity with monitoring, calibration, concept drift detection, and adaptive or online learning.
• Proficiency in SQL is desired.
• Knowledge about Linear Algebra, Combinatorial optimization is desired.
• Proficiency in scalable software design and development.
• Exposure to multimodal signals (text/image/metadata) is a plus, not required.

The expected salary range for this position is $140,000 USD to $170,000 USD annually. This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. The salary may be adjusted based on applicant's geographic location. The position is also eligible to receive performance bonus or commission and equity in the form of restricted stock units. This position is eligible to participate in the Company’s standard employee benefits programs, which currently include health care benefits; (2) retirement benefits; (3) the amount of paid days off (paid sick leave, parental leave, paid time off, or vacation benefits); (4) any other tax-reportable benefits. #LI-REMOTE

QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity or any other characteristics protected by law.

Please see QuinStreet’s Employee Privacy Notice here.