Staff Applied Scientist (Machine Learning)

Location: San Francisco, United States

Salary: $184,000–$299,812 per year for candidates based in the United States. Expected OTE: $204,000–$332,400 per year.

Company

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

What you will do

• Lead transformative initiatives across model training, model serving, data science production workflows, and ML infrastructure.
• Design, prototype, build, and operate distributed model training and serving systems.
• Develop model lifecycle management and pipelines that maintain hundreds of customer-specific models across regions.
• Set the technical vision, engineering standards, and production-readiness bar for ML systems.
• Collaborate with messaging, analytics, data platform, product, and engineering teams.
• Improve engineering quality through design and code reviews while mentoring senior engineers and data scientists.

Requirements

• 8+ years of experience building and operating production ML systems.
• Hands-on experience across data science, ML engineering, and MLOps, including model development, pipelines, services, and production operations.
• Experience deploying predictive models such as supervised and unsupervised models, neural networks, and recommenders using PyTorch or TensorFlow.
• Strong distributed systems fundamentals, with experience designing for scale, reliability, and cost.
• Technical leadership experience, including multi-quarter initiatives, cross-team direction, mentoring, and maintaining high individual output.
• Strong written and verbal communication skills with the ability to build consensus and guide decisions.

Nice to have

• Production experience with recommender systems, multi-armed bandits, or uplift modeling.
• Experience with MLflow or another model registry, Ray, feature stores, or ML observability.
• Experience with Python, Ruby on Rails, MongoDB, Redis, or Kubernetes.
• Experience in customer engagement, personalization, or marketing technology.

Culture & Benefits

• Collaborative, transparent, inclusive, and action-oriented work environment.
• Hybrid ways of working and a curated in-office experience focused on community and innovation.
• Equity grants, retirement and employee stock purchase plans, and flexible paid time off.
• Medical, dental, vision, life, disability, fertility, and equal paid parental leave benefits, varying by location.
• Professional development through career pathing, learning platforms, and an annual learning stipend.
• Employee resource groups, volunteer opportunities, and donation matching.

Hiring process

• AI-assisted tools may be used for application screening, interview scheduling, recording, and interview-note summaries.
• Recruiting teams remain responsible for hiring decisions; candidates may request information, opt out, or request manual review where applicable.