Senior Machine Learning Engineer, GenAI Security

8h•Remote

About The Position

Reddit is seeking a Senior Machine Learning Engineer to join the GenAI Security team. This team is responsible for protecting Reddit's GenAI usage across employee tools, internal agents, and user-facing systems. The role involves building zero-trust, defense-in-depth systems to secure AI traffic and adoption. A key focus is developing ML models to detect and prevent security risks like prompt injection, jailbreaks, data exfiltration, unsafe model behavior, and unauthorized agent actions. The Senior Machine Learning Engineer will lead model development for GenAI Security and establish strong ML practices within the SPACE organization, managing the entire ML lifecycle from problem definition to retraining.

Requirements

5+ years of experience building, training, evaluating, and deploying production ML or deep learning models.
Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.
Strong practical understanding of the full ML lifecycle: problem definition, data ETL, feature engineering, training, evaluation, deployment, monitoring, debugging, and retraining.
Experience building data pipelines and working with large-scale datasets.
Experience designing rigorous model evaluations, including precision/recall/F1, false positive analysis, threshold tuning, calibration, holdout sets, regression tests, and production-quality validation.
Experience shipping production-quality software, preferably in Python and/or Go.
Strong communication skills and ability to explain model behavior, risk tradeoffs, and technical decisions to cross-functional partners.
BS degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.

Nice To Haves

Applying ML to security, privacy, trust and safety, abuse prevention, adversarial ML, or GenAI security problems.
Training or fine-tuning neural text models for complex inputs such as long-context prompts, structured payloads, code-like content, multi-turn interactions, or tool calls.
Production MLOps or model serving systems such as Airflow, Ray, MLflow, Triton, ONNX, Kubernetes, or similar.
Improving model quality through labeling strategy, hard-negative mining, synthetic data generation, distillation, or active learning.

Responsibilities

Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals.
Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback.
Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit.
Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic.
Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces.
Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops.
Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows.
Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving.
Translate security goals into measurable model outcomes and help partners understand tradeoffs between risk reduction, latency, false positives, and product impact.
Provide technical direction to other engineers and serve as a go-to ML expert for GenAI Security and broader SPACE model needs.

Benefits

Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
Equity in the form of restricted stock units
Commission (depending on position offered)
Medical, dental, and vision insurance
Generous time off for vacation
Parental leave