Staff Machine Learning Engineer

Reddit is a community of communities that hosts open conversations on the internet. They are seeking a Staff Machine Learning Engineer to design and develop advanced machine learning models for online advertising platforms, while collaborating with various teams and providing technical leadership.

Responsibilities:

• Design, develop, and train advanced machine learning models, including deep neural networks, transformer-based architectures, and reinforcement learning systems, to power large-scale online advertising ranking and optimization platforms
• Lead the development and optimization of complex feature representations, including high-dimensional embeddings, contextual and temporal signals, and cross-session user behavior modeling
• Drive end-to-end model lifecycle execution, including system architecture design, large-scale experimentation, model deployment, performance monitoring, and iterative infrastructure improvements in production environments
• Collaborate closely with product, data, and infrastructure engineering teams to translate business objectives into scalable, statistically rigorous modeling solutions
• Conduct advanced experiment design and causal analysis to evaluate model impact and inform strategic decisions
• Provide technical leadership and mentorship to machine learning engineers and contribute to organization-wide modeling standards, best practices, and long-term technical strategy
• Shape the long-term modeling vision across multiple advertising domains, including conversion optimization, application advertising, shopping, and brand advertising

Requirements:

• Master's degree in Computer Science, Engineering (any field) or related quantitative discipline
• (3) three years of experience in the job offered or related occupation
• Python, Java, and Scala
• C++, Go, or Rust
• major machine learning frameworks and libraries
• applied statistics, hypothesis testing and experiment design for online machine learning systems
• large-scale data processing and analytics frameworks
• deployment and operation of production systems in containerized and distributed environments
• Designing and training advanced models, including deep neural networks, transformer-based architectures, and reinforcement learning models
• marketplace dynamics, such as real-time bidding (RTB) or pacing control systems
• developing and optimizing online advertising systems, including ad ranking, targeting, and market place
• providing technical leadership, mentorship, or guidance to other machine learning engineers