• Lead the technical enablement of machine learning teams in advanced use of the platform. • Drive and coordinate migrations of legacy models to the new platform with technical rigor and without regressions. • Systematically identify bugs, documentation gaps and structural adoption barriers — proposing and tracking resolutions directly with product teams. • Produce technical reference materials: usage architectures, production-grade code examples, runbooks and advanced guides. • Translate qualified community feedback into prioritized inputs for the platform roadmap. • Lead technical sessions, workshops and architecture reviews with engineering and data science teams. • Act as the technical authority and point of contact between the platform and its consumer teams.

Role Description We are searching for a talented Senior/Staff Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability. What you'll be doing: - Lead the creation and optimization of advanced machine learning algorithms—from developing new methods to refining existing techniques—to enhance advertising effectiveness and ROI using deep ML expertise. - Own the end-to-end development of production-grade ML models: write efficient, scalable code and collaborate with Data Engineers to deploy and integrate algorithms into live systems. - Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability; lead iterative improvements based on data-driven insights. Qualifications - 3+ years of industry experience - Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus. - Have the ability to take an ambiguously defined task, and break it down into actionable steps - Have a comprehensive understanding of statistics, optimization and machine learning - Are proficient in coding, data structures, and algorithms - Enjoy working in a friendly, collaborative environment with others Benefits - Highly competitive salary - Retirement/401K/Pension Savings globally - Competitive Paid time off packages including birthdays off! - Access to a comprehensive mental health care program - Health benefits from day one of employment - Work from home reimbursements - Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto - Robust training and onboarding program - Coverage and support of personal development initiatives (conferences, courses, books etc) - Access to StackAdapt programmatic courses and certifications to support continuous learning - An awesome parental leave program - A friendly, welcoming, and supportive culture - Our social and team events!

• Build core ML systems for a proactive AI product • Own end-to-end ML pipelines: data preparation, training, evaluation, inference • Collaborate with research, product, and engineering teams • Mentor and review work from other ML engineers

• Build and improve ML components across data, training, evaluation, and inference. • Fine-tune and adapt models as part of larger production systems. • Implement evaluation and testing to understand model behavior. • Help build and maintain data pipelines for real-world and synthetic data. • Debug model issues, performance problems, and production incidents. • Ship improvements iteratively and learn from real user feedback. • Work closely with senior ML engineers and product teams. • Work under real production constraints: latency, cost, reliability, and safety