Staff ML Engineer: Personalization & AI Platform

NewsBreak; United States; On-site; USD 230,000 - 300,000; Full time

Benefits offered by this job

Health, dental, and vision benefits

401(k) plan with company matching

Paid time off and holidays

Paid parental leave

FSA and commuter benefits

Team activity budget

Job summary

NewsBreak is seeking a Staff Machine Learning Engineer to provide technical leadership for our recommendation systems and AI initiatives. You will define technical direction for large-scale personalization systems, lead cross-team projects, and drive adoption of AI technologies in product capabilities and engineering workflows.

This role suits engineers who enjoy system-level thinking, mentoring others, and turning ambiguous problems into scalable solutions within a fast-growing company.

Qualifications

• 8+ years of industry experience building large-scale ML or recommendation systems.
• Deep expertise in recommendation systems and applied ML in production.
• Strong system design skills and ability to influence architecture across teams.
• Proven track record of technical leadership and cross-team collaboration.

Responsibilities

• Lead design of next-generation recommendation system architectures at scale.
• Drive model lifecycle management, experimentation, and system reliability.
• Partner with product, infra, and data teams to align technical strategy with business goals.
• Lead the application of LLMs and foundation models in recommendation, content intelligence, and user modeling.
• Champion AI-native development practices and tooling.

Skills

Large-scale ML systems

System design

Technical leadership

Recommendation systems

Tools

LLMs

Foundation models

Job description

NewsBreak is seeking a Staff Machine Learning Engineer to provide technical leadership for our recommendation systems and AI initiatives. You will define technical direction for large-scale personalization systems, lead cross-team projects, and drive adoption of AI technologies in product capabilities and engineering workflows.

This role suits engineers who enjoy system-level thinking, mentoring others, and turning ambiguous problems into scalable solutions within a fast-growing company.