Reinforcement Learning Engineer Salary

Based on 252 Reinforcement Learning listings with published compensation (592 total jobs)

Reinforcement Learning engineer salaries span a wide range depending on experience level, company size, and location. Roles at the 75th percentile ($300k) typically go to senior and lead engineers at frontier AI labs, well-funded startups, and FAANG-tier teams shipping Reinforcement Learning features in production. Entry-level and mid-level Reinforcement Learning roles cluster around the 25th percentile ($213k).

Compensation figures below are computed from 252 AI Dev Jobs listings with published salary ranges — a subset of the 592 total open Reinforcement Learning roles. Ranges reflect base salary in USD/year; total comp (equity, bonus, signing) is typically 1.3–2× base at top-paying companies. Remote roles increasingly match in-office rates for this skill.

How this data is collected

AI Dev Jobs scrapes curated job feeds (Greenhouse, Ashby, Lever) from 538 ATS sources across 489 AI companies daily. Listings are filtered for AI/ML relevance; generalist roles are excluded. Salary figures come directly from the publicly posted compensation ranges on each listing — we do not estimate or impute. If a role doesn't publish a salary, it is excluded from these statistics but still appears in the job listings.

Data is refreshed every 24 hours. The percentile breakdowns above (p25, p50 median, p75) are computed over the midpoint of each published range. Experience level percentiles use the same midpoint method, grouped by the experience_level field on the listing. City-level figures require at least 3 open roles in that city for Reinforcement Learning.

Raw data available via the REST API or MCP server.

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