Staff Machine Learning Engineer, ML Platform (AI)

Location: New York City, United States; hybrid work

Salary: $184,000–$314,000 per year base pay for candidates based in the United States; expected OTE of $204,000–$348,000 including bonus or commission.

Company

hirify.global is a customer engagement platform that helps brands deliver personalized experiences through messaging, journey orchestration, and AI-powered decisioning.

What you will do

• Drive transformative initiatives for production ML infrastructure, including queueing, orchestration, deployment, cloud identity, and infrastructure retirement.
• Design, build, and operate multi-region model-serving fleets, customer-specific model training pipelines, and CI/CD deployment tooling.
• Set the technical vision and production quality standards for model training, deployment, serving, observability, reliability, and cost efficiency.
• Lead incident response and complex infrastructure initiatives from design through production.
• Coordinate initiatives across teams that share infrastructure, deployment tooling, and data systems.
• Improve engineering quality through design and code reviews, production readiness, mentorship, and technical leadership.

Requirements

• 8+ years of experience building and operating distributed systems in production.
• Hands-on experience with production ML workloads, such as training pipelines, model serving, feature systems, or ML platform tooling.
• Experience leading multi-quarter initiatives across teams and mentoring senior engineers and data scientists.
• Deep knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and cost optimization.
• Experience with deployment and operations, CI/CD, infrastructure as code, and production reliability.
• Strong written and verbal communication skills with the ability to build consensus and guide technical decisions.

Nice to have

• Experience with Celery, RabbitMQ, Kafka, or Ray.
• Experience with MLflow, model registries, feature stores, or ML observability.
• Experience with Python, Ruby on Rails, MongoDB, Redis, and Kubernetes.
• Experience with SOX or HIPAA compliance, customer engagement, personalization, or marketing technology.

Culture & Benefits

• Hybrid ways of working with a curated in-office experience.
• Competitive compensation that may include equity, retirement plans, and an employee stock purchase plan.
• Flexible paid time off and comprehensive medical, dental, vision, life, and disability benefits.
• Fertility benefits, equal paid parental leave, professional development, formal career pathing, and a yearly learning stipend.
• Employee Resource Groups, volunteer opportunities, donation matching, and a collaborative culture.