Senior Machine Learning Engineer, GenAI Security

Details

The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. The team builds zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. This role focuses on developing practical machine learning models to detect and prevent prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions.

The role owns the full machine learning lifecycle, including problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining.

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 security problems, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain using production feedback.
• Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where appropriate.
• 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 with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to integrate security models into production workflows.
• Work with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed.
• Translate security goals into measurable model outcomes and explain tradeoffs between risk reduction, latency, false positives, and product impact.
• Provide technical direction to other engineers and serve as an ML expert for GenAI Security and broader SPACE model needs.

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, including 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.
• Bachelor’s degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.

Preferred Experience

• Applying ML to security, privacy, trust and safety, abuse prevention, adversarial ML, or GenAI security problems.
• Training or fine-tuning neural text models for 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.

Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Global benefit programs supporting workspace, professional development, caregiving, and other needs.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Generous paid parental leave.
• Eligibility for equity in the form of restricted stock units.

Compensation

The base salary range for this position is $216,700–$303,400 USD. The role may also be eligible for equity and, depending on the position offered, a commission.