Machine Learning Engineer - Ad Ecosystems

Summary

Join Haus, a marketing science platform revolutionizing advertising, as a Machine Learning Engineer. You will lead impactful projects, designing and building systems to reshape the advertising ecosystem. This role involves developing complex intervention systems, advanced marketing planning tools, and optimization engines powered by machine learning and causal inference. You will drive initiatives from concept to delivery, implement probabilistic techniques, build and maintain ML systems, and collaborate with cross-functional teams. The ideal candidate possesses a strong background in machine learning engineering, adtech experience, and proficiency in programming languages. Haus offers a competitive salary, comprehensive benefits, and the opportunity to make a significant impact.

Requirements

• BS or MS in Computer Science, Engineering, Mathematics or related field
• Must have 3+ years of work experience in Adtech industry
• Must have 5+ years of working experience as a Machine Learning Engineer, building and operating production ML systems
• Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design
• Experience working with cross-functional teams(product, science, product ops etc)
• Proficiency in one or more object-oriented programming languages (e.g. Python, Go, Java, C++)

Responsibilities

• Drive initiatives from concept to final product delivery, ensuring seamless end-to-end execution: lead or contribute to the design, development, optimization, and product ionization of machine learning (ML) solutions for complex and high-impact problems
• Implement probabilistic techniques into reusable statistical libraries, including bootstrapping, statistical tests, and ML models/regressions
• Build and maintain the ML systems that power Haus’ product lines
• Review code and designs of teammates, providing constructive feedback
• Lead and collaborate with engineering and cross-functional partners across product, engineering, and science teams to drive system development from ideation to production

Preferred Qualifications

• Exposure to LLMs or AI Agentic field
• Experience in modern deep learning architectures and probabilistic modeling
• Expertise in the design and architecture of ML systems and workflows
• Experience Data Science or machine learning approaches in marketing and growth

Benefits

• Competitive salary and startup equity
• Top of the line health, dental, and vision insurance
• 401k plan
• Provide you with the tools and resources you need to be productive (new laptop, equipment, you name it)
• Small team with big impact on the overall output