Staff Machine Learning Engineer
Staff Machine Learning Engineer building and operating production ML systems for causal marketing measurement, optimization, and planning. The role requires deep statistical and machine learning expertise, production programming experience, cross-functional collaboration, and technical mentorship.
About the job
Responsibilities
- Drive initiatives from concept through final product delivery, including the design, development, optimization, and productionization of machine learning solutions.
- Implement probabilistic techniques in reusable statistical libraries, including bootstrapping, statistical tests, and machine learning models and regressions.
- Build and maintain the machine learning systems powering Haus product lines, especially cMMM.
- Drive the design and implementation of AI agentic workflows for machine learning pipelines, including model validation.
- Review teammates’ code and designs, providing constructive feedback.
- Collaborate with product, engineering, data science, applied science, data engineering, and other cross-functional teams.
- Mentor machine learning engineers and raise the organization’s machine learning standards.
Requirements
- PhD or equivalent experience in Computer Science, Engineering, Mathematics, or a related field.
- 10+ years of industry experience focused on building and operating production machine learning systems.
- Experience with exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
- Experience working with cross-functional teams.
- Proficiency in one or more object-oriented programming languages, such as Python, Go, Java, or C++.
Nice-to-haves
- Experience with modern deep learning architectures and probabilistic modeling.
- Expertise designing and architecting machine learning systems and workflows.
- Experience with optimization techniques, including reinforcement learning, Bayesian methods, and multi-armed bandits.
- Experience with MLflow.
- Experience applying data science or machine learning to marketing and growth.
Compensation and Benefits
- Equity participation.
- Health, dental, and vision insurance with multiple plan options.
- Flexible paid time off.
- Work-from-home stipend.
- Events and offsites.
- Free lunch when working from the office.
- New parent leave.
Skills
Machine Learning, Python, Go, Java, C++, Causal Inference, Statistical Modeling, Hypothesis Testing, Experimental Design, Probabilistic Modeling, Deep Learning, Reinforcement Learning, Bayesian Methods, Multi-Armed Bandits, MLflow
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