Remote Senior ML Engineer for Ranking & Recommendations

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

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.