Quick summary
- Work type
- Remote
- Location
- Remote
- Salary
- $216,700–$303,400 / yr
- Posted
- 77 days ago
- Freshness
- Confirmed live 2 days ago
Market check
Salary context
How this pay compares to similar roles
This role pays more than 79% of similar roles. Most pay $201,150–$254,800 — the shaded band above. At the midpoint, this role pays about $260k versus about $228k for comparable roles.
Based on 240 similar postings.
Employer
About Reddit
Reddit is a social news aggregation and discussion platform where users share content, vote on posts, and engage in community conversations across thousands of interest-based forums called subreddits.
Reddit currently has 77 open roles on FindRole.
Listed pay typically runs $217,000–$303,400 across 77 roles with salary data.
Most-posted roles
- Software Engineer 19
- Data Scientist 8
- Machine Learning Engineer 5
- Frontend Engineer 4
- Machine Learning Systems Engineer 4
At a glance
TL;DR · Machine Learning Engineer, Ads Optimization
Machine Learning Engineer, Ads Optimization joins the Ads Optimization team to build and evolve auction, bidding, and budgeting systems for the platform's revenue engine. You will design and implement optimization algorithms for auctions, bidding strategies, and pacing to balance advertiser performance with user experience and marketplace efficiency. Responsibilities include developing models to compute bids for various objectives like CPC or ROAS, managing budget pacing across campaigns, and translating complex marketplace goals into concrete technical constraints. The role requires proficiency in Python, Java, or Go, along with experience in scalable data processing using Spark, Kafka, Airflow, BigQuery, and Redis. Ideal candidates possess strong math and optimization skills to implement custom logic like gradient-based methods. This position addresses the core challenge of managing high-scale ad auctions and ensuring marketplace quality through sophisticated bidding and pacing systems.
What does a Machine Learning Engineer earn in Remote?
Median $229700 from 72 postings across 27 companies.
Skills
What you'll do
- Design and implement optimization algorithms for auctions, bidding strategies, and pacing.
- Develop models to compute bids based on various objectives like CPC, CPA, and ROAS.
- Build systems to pace budgets smoothly across accounts while preventing overspend or underspend.
- Allocate spend and auction participation intelligently across different segments, surfaces, and time zones.
- Translate product goals into concrete optimization problems involving ROI, revenue, and user experience.
- Own the end-to-end lifecycle of systems from problem formulation to production deployment.
- Set technical direction for key parts of the bidding, auction, and pacing stack.
- Mentor other engineers while remaining hands-on with complex multi-quarter initiatives.
What we're looking for
- 3–5+ years of experience building, deploying, and operating machine learning systems in production.
- Strong programming skills in Python, Java, Go, or similar languages with solid software engineering fundamentals.
- Experience designing scalable data processing systems using tools like Spark, Kafka, Airflow, BigQuery, or Redis.
- Ability to translate ambiguous product or business problems into solutions that improve measurable metrics.
- Advanced math and optimization skills, including experience with gradient-based methods and constraint handling.
- Degree or equivalent background in a quantitative field such as math, physics, finance, economics, or operations research.
- Experience in optimization-heavy domains like bidding, auctions, pacing, pricing, logistics, or quantitative finance.
- Preferred experience with advertising systems, online marketplaces, search/ranking systems, and real-time decision environments.
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