Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing, building, and deploying advanced machine learning systems for safety, security, and intelligence applications with an accent on multimodal classification, model evaluation, and agentic workflows. Focus on solving complex, ambiguous problems at the frontier of AI safety and security through rapid experimentation and production-ready engineering.

Location: Must be based in the U.S. (Fully remote)

Salary: $130,000–$200,000

Company

hirify.global provides a safety and threat-intelligence layer for frontier AI labs, unicorns, and Fortune 10 companies.

What you will do

• Design, train, and deploy ML models across text, image, audio, and multimodal domains.
• Develop classification systems for safety, security, and abuse detection.
• Benchmark and evaluate large language models and multimodal systems.
• Contribute to model distillation, optimization, and fine-tuning efforts.
• Build agentic systems and automated workflows for red teaming and research.
• Own ML projects from prototyping through production deployment and monitoring.

Requirements

• 3–5+ years of professional experience building and deploying ML systems.
• Strong proficiency in Python and frameworks like PyTorch or TensorFlow.
• Expertise in Computer Vision or NLP modalities.
• Experience with MLOps tools (Docker, Kubernetes, CI/CD, MLflow).
• Experience with cloud platforms (GCP preferred, AWS, or Azure).
• Must be based in the U.S.

Nice to have

• Experience with frontier language models and AI safety evaluations.
• Background in cybersecurity, trust and safety, or threat intelligence.
• Experience with RAG, LangChain, LlamaIndex, or AI agent frameworks.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Generous PTO and paid holiday schedule.
• Performance-based annual bonus.
• Support for professional development, conferences, and continuing education.
• Fully remote work environment.