Director, Machine Learning Engineer, Content (AI)

Location: Bellevue, Los Angeles, Palo Alto, San Francisco, Seattle, or New York; office work expected 4+ days per week.

Salary: $334,000–$500,000 annually in Zone A; $317,000–$475,000 annually in Zone B; $284,000–$425,000 annually in Zone C, plus eligibility for RSUs.

Company

Technology company operating hirify.globalchat, Specs, Bitmoji, Saturn, and other digital services focused on visual communication and human-centered computing.

What you will do

• Set the multi-year machine learning strategy for recommendation and ranking, content understanding, production reliability, and experimentation.
• Oversee day-to-day operations of Content Machine Learning teams across multiple offices.
• Develop organizational goals and drive the technical and organizational roadmap.
• Partner with executives, Finance, Product, and Engineering to deliver high-quality products.
• Guide architecture and implementation decisions for scalable, reliable, and cost-effective engineering solutions.
• Build and scale teams of software engineers, machine learning engineers, and technical leaders while mentoring managers, directors, and senior contributors.

Requirements

• Bachelor’s degree in a relevant technical field or equivalent practical experience; alternatively, a Master’s degree with 9+ years of post-graduate software development experience or a PhD with 6+ years of post-graduate software development experience.
• 10+ years of software engineering experience after a Bachelor’s degree, or the equivalent experience associated with the advanced-degree paths.
• 5+ years of experience leading a large team at scale and managing engineering with a focus on efficiency.
• Experience working with machine learning, AI, and ranking systems.
• Strong understanding of machine learning, deep learning approaches, and algorithms.
• Experience leading and developing engineers with diverse backgrounds, skills, and perspectives.
• Ability to partner with cross-functional executives and management across a geographically distributed organization.

Nice to have

• Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments.
• Experience with machine learning and generative recommendations.
• Experience with high-scale ranking and recommendation systems.

Culture & Benefits

• Default-together approach with in-person office collaboration expected 4+ days per week.
• Paid parental leave and comprehensive medical coverage.
• Emotional and mental health support programs.
• Compensation packages including long-term equity participation through RSUs.
• Equal opportunity employment and commitment to diverse backgrounds and voices.