Principal Machine Learning Architect, Sift

• Proven experience building large-scale ML systems in production environments
• Familiarity with tools like Flink, Spark, PyTorch, TensorFlow, or similar frameworks
• Proficiency in not only Python, but also Java, C++, or similar languages
• Knowledge of industry best practices for deploying, maintaining, and scaling ML systems in production
• Experience in high-impact areas such as ad-tech, recommendation systems, personalization, search ranking, or gaming
• Strong understanding of modern ML engineering trends and challenges, including but not limited to model monitoring, drift detection, and retraining strategies
• Knowledge of GenAI, including LLMs, as well as the trends and challenges of building GenAI applications
• Ability to align and lead cross-functional teams on large-scale architectural initiatives. Able to partner, energize and inspire within and across the organization
• Demonstrated success in working with diverse stakeholders and fostering alignment around technical and business objectives
• Ability to provide guidance or mentor junior engineers
• Strong critical thinking and ability to approach ambiguous problems systematically
• Curiosity and openness to understand the business impact of technical decisions
• Excellent communication and storytelling skills to articulate architectural vision and influence stakeholders at all levels
• Ability to engage in constructive technical discussions and drive consensus
• Ability to evangelize our data and AI externally, such as with customers, partners, and in the industry

Desirable

• We are seeking a highly skilled and experienced Machine Learning Architect to lead the design, implementation, and continual evolution of large-scale, production-grade ML systems
• This role requires a technical leader who will take an active role in defining and leading our teams towards our vision, ensuring that we remain at the forefront of AI and ML engineering while continuing to deliver real, measurable value to our customers
• You will work cross-functionally with engineering, data science, product, and leadership teams to align our ML architecture with business goals and emerging industry best practices
• Architect scalable, reliable, and low-latency (150ms) ML systems for both online and offline use cases. Think of PBs of data for model training, and 10s of thousands of scoring QPS
• Ensure systems meet strict performance, latency, and reliability requirements
• Evaluate and incorporate cutting-edge ML trends and technologies while aligning them with the company’s current architecture and goals
• Define a roadmap to transition the ML ecosystem to a more advanced, future-proof state
• Work closely with stakeholders across engineering, product, and data science teams to align technical designs with business priorities
• Create interfaces (programmatic and organizational) that enable collaboration and coordination across teams and systems
• Establish and enforce best practices for maintaining consistent ML model performance in production
• Develop monitoring systems, metrics, and processes to ensure model quality and reliability over time
• Lead large-scale initiatives, such as transitioning to next-generation architectures, and ensure alignment across diverse engineering teams
• Provide mentorship and technical guidance to engineers to foster a culture of excellence
• Develop a deep understanding of business and customer KPIs
• Collaborate with customer-facing teams to understand use cases and ensure the ML systems deliver real-world impact
• Represent the innovation of our data science and ML in the industry