Senior Machine Learning Engineer, Ad Serving

Roku•Boston, MA

23h•Hybrid

About The Position

This role will drive improvements in Roku Exchange efficiency by applying advanced data analytics and machine learning techniques to optimize pricing, allocation, and auction across the marketplace. For Massachusetts Only - The estimated annual salary for this position is between $195,500 - $352,100 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

Requirements

10+ years of industry experience applying machine learning and data science to solve complex, mission-critical real-world problems
Deep expertise in statistics, machine learning, and optimization techniques
Perform as a staff+ technologist on complex, revenue-critical, large-scale distributed ML systems
Hands-on experience building and deploying ML models in production, including feature engineering, model serving, monitoring, and continuous improvement
Solid software engineering skills in languages such as Python, SQL, and Java/Scala
Strong CS fundamentals with the ability to translate ideas into clean, efficient code with ease
Excellent written and verbal communication and collaboration skills
Proven track record of leading cross-functional teams and initiatives

Nice To Haves

Publications in leading peer-reviewed conferences or academic journals are a plus
Expertise in advertising is a plus

Responsibilities

Translate ambiguous business problems into clear hypotheses, measurable objectives, and actionable strategies
Develop advanced ML models and research-driven methodologies to drive product innovation and improve business outcomes
Design and run live experiments to prototype improvements and validate their effectiveness
Build production-grade ML systems that operate reliably in large-scale, low-latency ad serving environments
Partner with cross-functional stakeholders to define, plan, and drive the ML strategy for Ad Serving
Provide technical leadership and mentorship in machine learning, experimentation frameworks, and applied research best practices