Senior Machine Learning Engineer (GenAI Security)

TL;DR

Senior Machine Learning Engineer (GenAI Security): Building and improving security-focused ML models for hirify.global’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection, and neural network-based security signals with an accent on zero-trust defense-in-depth systems. Focus on owning the full ML lifecycle from data ETL and feature engineering to deployment, monitoring, and retraining while designing rigorous evaluation suites for adversarial examples and production traffic.

Location: Remote - United States

Salary: $216,700 - $303,400 USD

Company

hirify.global is a community of communities built on shared interests with 100,000+ active communities and approximately 126 million daily active unique visitors.

What You’ll Do

• Build and improve security-focused ML models for GenAI traffic including guardrails, semantic classifiers, and anomaly detection.
• Own end-to-end model development: define problems, assemble datasets, build ETL pipelines, engineer features, train, evaluate, deploy, monitor, and retrain models.
• Use deep learning architectures like neural networks, transformers, sequence models, embeddings, and model distillation.
• Design evaluation suites for adversarial examples, hard negatives, long-context inputs, and production traffic.
• Optimize model precision, recall, latency, cost, calibration, and reliability for production.
• Build MLOps workflows including training pipelines, model lineage, dashboards, and retraining loops.
• Partner with ML Infrastructure, LLM Gateway, Safety, Privacy, and other teams to integrate models into production.

Requirements

• 5+ years building, training, evaluating, and deploying production ML or deep learning models
• Hands-on with PyTorch, TensorFlow, or similar frameworks
• Strong understanding of full ML lifecycle: data ETL, feature engineering, training, evaluation, deployment, monitoring
• Experience with data pipelines and large-scale datasets
• Rigorous model evaluations including precision/recall, false positives, calibration, holdout sets
• Ship production software in Python and/or Go
• BS in Computer Science, Machine Learning, or equivalent
• Strong communication to explain models and tradeoffs

Nice to have

• ML for security, privacy, trust & safety, adversarial ML, or GenAI security
• Training neural text models for long-context prompts, structured payloads, multi-turn interactions
• Production MLOps: Airflow, Ray, MLflow, Triton, Kubernetes
• Improving models via labeling, hard-negative mining, synthetic data, distillation, active learning

Culture & Benefits

• Comprehensive healthcare benefits and income replacement programs
• 401k with employer match
• Global benefits for workspace, professional development, caregiving
• Family planning support and gender-affirming care
• Mental health & coaching benefits
• Flexible vacation, paid volunteer time off, generous paid parental leave