Staff Machine Learning Engineer

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Job Duties: 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. Full-time telecommuting is an option.

Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and (3) three years of experience in the job offered or related occupation.

Special Skill Requirements: 1) Python, Java, and Scala; 2) C++, Go, or Rust; 3) major machine learning frameworks and libraries; 4) applied statistics, hypothesis testing and experiment design for online machine learning systems; 5) large-scale data processing and analytics frameworks; 6) deployment and operation of production systems in containerized and distributed environments; 7) Designing and training advanced models, including deep neural networks, transformer-based architectures, and reinforcement learning models; 8) marketplace dynamics, such as real-time bidding (RTB) or pacing control systems; 9) developing and optimizing online advertising systems, including ad ranking, targeting, and market place; 10) providing technical leadership, mentorship, or guidance to other machine learning engineers. Any suitable combination of education, training and/or experience is acceptable. Full-time telecommuting is an option.