Senior Machine Learning Engineer, GenAI Security

Reddit

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$216,700–$303,400 / yr
Posted
today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $212k
This role $260k
$155k most similar roles pay here $319k

This role pays more than 82% of similar roles. Most pay $174,990–$249,753 — the shaded band above. At the midpoint, this role pays about $260k versus about $212k 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 72 open roles on FindRole.

Listed pay typically runs $217,000–$303,900 across 66 roles with salary data.

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View all roles at Reddit

At a glance

TL;DR · Senior Machine Learning Engineer, GenAI Security

As a Senior Machine Learning Engineer on Reddit’s GenAI Security team, you will lead the development of security-focused ML models to protect Reddit's AI traffic and ensure secure GenAI adoption. Your responsibilities include defining problems, building ETL pipelines, engineering features, training models, deploying them in production, monitoring performance, and retraining based on feedback. You will work with modern deep learning frameworks like PyTorch and TensorFlow, design robust evaluation suites for adversarial examples, and build repeatable MLOps workflows using tools such as Airflow and MLflow. This role requires hands-on experience with large-scale datasets, rigorous model evaluations, and a strong background in the full ML lifecycle. You will collaborate closely with various teams to integrate security models into production workflows and translate security goals into measurable outcomes.

What you'll do

  • Build and improve security-focused ML models for Reddit’s GenAI traffic.
  • Own the full machine learning lifecycle from problem definition to retraining.
  • Design rigorous evaluation suites for adversarial examples and production traffic.
  • Improve model precision, recall, latency, cost, calibration, and operational reliability.
  • Build repeatable MLOps workflows including training pipelines and artifact management.

What we're looking for

  • 5+ years of experience in building, training, and deploying production ML or deep learning models.
  • Hands-on expertise with modern ML frameworks like PyTorch, TensorFlow, or similar tools.
  • Strong understanding of the full machine learning lifecycle from problem definition to model retraining.
  • Experience in designing rigorous evaluation suites for adversarial examples and real production traffic.
  • Ability to build repeatable MLOps workflows including training pipelines and artifact management.
  • BS degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.

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