Senior Machine Learning Engineer, Causal & Decision Systems

This is a fully remote position, open to applicants in Texas.

📋 Description

• Develop closed-loop decision-making systems utilizing machine learning for pricing and various consumer-business decisions.

• Assess causal responses and measure uncertainty.

• Select actions, generate valuable information, observe results, and refine policies.

• Review alternative policies and implement systems within established guidelines.

• Collaborate on causal and diverse treatment-effect modeling, uncertainty assessment, contextual bandits, active learning, sequential decision-making, policy learning, constrained optimization, counterfactual evaluation, experimentation, production ML infrastructure, monitoring, and automated deployment.

• Deliver measurable economic improvements in controlled experiments.

• Generalize systems across different businesses and automate commercial decisions safely.

• Leverage the decision-system capability across a range of businesses and increasingly expansive commercial decisions.

⛳️ Requirements

• Outstanding technical skills and judgment.

• Proven experience in various areas of machine learning and statistical modeling, causal inference and experimentation, recommendations, advertising, pricing, marketplace, credit, or other decision-making systems.

• Familiarity with bandits, reinforcement learning, optimization, active learning, uncertainty assessment, counterfactual evaluation, or production ML systems.

• Proficiency in Python and SQL.

• Experience handling large behavioral datasets.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health benefits, including medical, dental, and vision coverage.

• Opportunities for professional development and growth.

• Flexible work hours and remote work options.