Machine Learning Engineer, Ads Optimization & Ads Marketplace Quality

Details

Reddit is a community of communities built on shared interests, passion, and trust. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit hosts large-scale, authentic conversations across the internet.

Team Description

This role sits in the Ads Optimization and Ads Marketplace Quality (AMQ) organizations, responsible for the health and performance of Reddit’s ads marketplace. The teams focus on:

• Designing auction and bidding mechanisms that decide which ads show to which users and at what price.
• Building optimization systems that help advertisers achieve goals (e.g., conversions, ROAS) under budget and delivery constraints.
• Ensuring marketplace quality by improving user experience with ads, fighting ad blindness, and increasing valuable ad opportunities.

You will collaborate closely with Product, Data Science, and Infra partners across Reddit Ads.

Role Description

You will build and evolve the auction, bidding, and budgeting systems that power Reddit Ads. Responsibilities include designing and implementing optimization algorithms and owning systems end-to-end: from problem formulation and algorithm design to experimentation, production deployment, and iteration.

Hiring is open for IC3 and IC4 levels:

• IC3: strong individual contributors who can independently own scoped projects, ship models and services, and contribute to experimentation and measurement.
• IC4: lead more complex or multi-quarter initiatives, set technical direction for key parts of the bidding/auction/pacing stack, and mentor other engineers while remaining hands-on.

Responsibilities

Auction, Bidding, and Pacing Systems

• Design and implement models and policies to compute bids for different optimization objectives (CPC, CPA, ROAS-based strategies).
• Pace budgets smoothly over time across accounts, campaigns, and ad groups while preventing overspend or underspend.
• Allocate spend and auction participation intelligently across segments, surfaces, and time zones.
• Translate product and marketplace goals into concrete optimization problems and constraints (ROI, revenue, delivery smoothness, fairness, user experience).

Marketplace Quality and Optimization

• Improve ad matching and ranking by incorporating new quality and relevance signals into bidding and auction decisions.
• Inform policies around ad load and eligibility to protect user experience while increasing high-quality ad opportunities.
• Integrate new bid strategies and pacing mechanisms into the broader ads ecosystem and measurement stack.

Required Qualifications

• 3–5+ years of experience building, deploying, and operating machine learning systems in production (for IC4, typically 5+ years).
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals.
• Experience designing scalable data processing systems (examples: Spark, Kafka, Airflow, BigQuery, Redis).
• Demonstrated ability to translate ambiguous product or business problems into solutions and to improve measurable metrics.

Additional expectations for strong bidding/auction candidates (especially IC4):

• Strong math and optimization skills (degree or equivalent background in quantitative fields such as math, physics, quantitative finance, economics, operations research, or similar).
• Experience in optimization-heavy domains (bidding/auctions, pacing, pricing, logistics optimization, quantitative finance).
• Comfort implementing custom optimization logic (gradient-based methods, constraint handling), not just applying black-box tooling.

Preferred Qualifications

• Experience with advertising/auction systems, online marketplaces, or search/ranking systems at scale (bidding, pacing, budget optimization, auction design, mechanism design, marketplace quality).
• Familiarity with large-scale, real-time decision systems and low-latency production environments.
• Background in feature engineering, model optimization, and production monitoring for ML systems.
• Experience collaborating with cross-functional partners (Product, DS, Eng) in Ads or marketplace contexts and leading projects from design through rollout.
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Operations Research, Applied Math, or a related quantitative field.

Potential Teams

• Ads Optimization (bid strategies, conversion/ROAS optimization, pacing and budget allocation)
• Ads Marketplace Quality (ad matching, load, and quality controls)

Benefits

• Comprehensive healthcare benefits and income replacement programs
• 401(k) with employer match
• Global benefit programs (workspace, professional development, caregiving support)
• Family planning support and gender-affirming care
• Mental health & coaching benefits
• Flexible vacation & paid volunteer time off
• Generous paid parental leave

Pay Transparency

Base salary range for this US-based position: $185,800 - $303,400 USD. The role may also be eligible for equity (restricted stock units) and, depending on position, a commission. Final offers are determined by skills, experience, and other factors.

Interview Recording & Privacy

In select roles and locations, interviews may be recorded, transcribed, and summarized by AI; candidates can opt out prior to scheduled interviews. The posting describes categories of personal information collected during interviews and points to Reddit's Candidate Privacy Policy for details.