Senior Staff Machine Learning Engineer, Ads Ranking

Reddit is a community-driven platform built around shared interests, passion, and trust. The company is seeking a Senior Staff Machine Learning Engineer to advance agentic AI applications for improving machine learning model quality and development velocity. The role involves leading modeling workflows, designing evaluation systems, partnering across technical teams, and setting organization-wide technical direction.

Responsibilities:

• Develop advanced ML models and the agentic workflows that help teams design, train, evaluate, and improve them
• Use tools such as Claude, Cursor, and comparable AI-assisted development systems to investigate model behavior, generate and test hypotheses, automate repetitive analysis, and improve code and experiments
• Build reliable loops for data and label analysis, feature and embedding development, architecture comparison, hyperparameter optimization, error analysis, and experiment readouts
• Design evaluation harnesses that measure both model outcomes and agent/workflow quality, including correctness, reproducibility, regressions, cost, and latency
• Partner with product, data science, ML infrastructure, and engineering teams to connect modeling improvements to user and business outcomes
• Set technical direction across teams, mentor engineers, and raise the bar for modeling rigor and AI-assisted engineering

Requirements:

• 9+ years of experience in ML engineering, applied ML, or a related field, with substantial production impact
• Senior Staff-level technical leadership and a record of influencing direction across teams
• Deep modeling expertise and strong fundamentals in data, objectives, architectures, optimization, evaluation, and experimentation
• Concrete examples of using agentic AI or AI coding tools to produce better ML outcomes—not just faster code generation
• Ability to design guardrails and evaluations that make autonomous or semi-autonomous workflows trustworthy
• Strong coding ability in Python and fluency with modern ML frameworks and data tooling
• Clear, concise communication and a collaborative, low-ego approach to technical leadership