• Lead ML Research and Development: Drive the research, development, and optimization of machine learning models, focusing on solving real-world business problems through advanced ML techniques. • Architect Novel Training and Fine-Tuning Methodologies: Design, implement, and iterate on advanced training protocols, fine-tuning processes, and optimization strategies, particularly for Language Models (LLMs). • Evaluate Model Performance and Innovation: Develop and refine techniques for assessing and enhancing the effectiveness of ML models, focusing on accuracy, scalability, and adaptability to dynamic enterprise requirements. • Feedback System Design for Continuous Learning: Create systems that incorporate user and system feedback to iteratively improve model performance over time. • Cross-Functional Collaboration: Work closely with product teams and domain experts to translate business needs into research questions and actionable ML strategies. • Stay Current on ML Advancements: Actively monitor the latest research in ML and NLP, integrating cutting-edge practices and methodologies into our development pipeline. • Mentor and Guide Team Members: Provide technical guidance to junior researchers, fostering a culture of continuous learning, experimentation, and research-driven development.

• Increase quality leads at efficient costs, testing strategies on a daily, weekly and monthly basis. • Be a part of the ongoing conversation of how to best execute and measure multi-channel digital marketing campaigns across search, display, social media, video, email, and other channels. • Execute online marketing campaigns and tests, including implementation, optimization, budget management, and analysis. • Support customer acquisition and engagement via paid digital marketing, including Google, Bing, YouTube, Capterra, Google Display Network, programmatic channels, etc. • Launch, and track frequent ad copy, landing page, and other creative tests using some of the latest testing tools and methodologies. • Analyze SEM & Paid Social performance, making recommendations and executing optimizations. • Assist in managing multiple advertising accounts. • Support creation of reports to measure campaign performance and show ROI of efforts.

• Lead, develop, and mentor the Platform Security team, setting direction, managing performance, and ensuring strong communication and execution across distributed time zones. • Design, implement, and operate cloud security controls for AWS, GCP, and Azure to protect infrastructure, services, and applications from evolving threats. • Partner with engineering and product leadership to influence architecture decisions, define security requirements, and ensure alignment with Affirm’s technical strategy. • Strengthen container security by guiding secure design and operation of containerized environments using Docker, Kubernetes, and related ecosystem tooling. • Drive adoption of DevSecOps practices by embedding automated security checks, workflows, and guardrails into CI/CD pipelines and developer tooling. • Communicate complex security risks, tradeoffs, and recommendations to technical and non-technical stakeholders with clarity, precision, and authority. • Develop and mature the platform security roadmap, identifying long-term risks, investments, and capabilities needed to strengthen Affirm’s cloud posture. • Define, maintain, and enforce baseline security configurations, standards, and operational processes for cloud platforms, systems, and applications. • Create and maintain security metrics and dashboards that provide meaningful insights into control effectiveness, program maturity, and areas needing investment. • Support budget planning, resource allocation, and team development, ensuring the program can scale effectively and deliver strong outcomes over time.

• Design and build platform capabilities that deliver reliable, high-value features with safety, precision, and user focus. • Collaborate closely with product managers, designers, and fellow engineers to create new features and improve existing ones. • Approach the platform as a product: maintain a clear understanding of customer needs, identify friction points, and take ownership of outcomes with metrics-driven decision making (KPIs, OKRs, and North Star metrics). • Use data to inform decisions, measure impact, and drive improvements through empirical evidence. • Take ownership across all phases of development, from design to production, and monitor system performance in live environments. • Continuously improve the flow of work from idea to production, using data to identify and remove friction. • Write clean, efficient, and well-documented code following best practices. • Build and maintain APIs, and integrate with third-party services. • Ensure application performance, quality, and responsiveness across platforms. • Participate in code reviews, testing, and debugging to maintain high-quality deliverables. • Mentor other engineers and contribute to their growth. • Contribute to architectural decisions and help define technical standards and best practices. • Stay up to date with emerging technologies and suggest improvements to enhance development processes.