Staff ML Engineer: Build Production-Grade AI Systems

HAUS; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Flexible PTO

Equity

Health insurance

WFH stipend

Events & Offsites

Free Lunch

New Parent Leave

Job summary

HausHaus is seeking a senior ML Engineer to drive high-impact projects in advanced marketing planning, analysis, and optimization. You will collaborate with applied scientists, data scientists, and engineers to deliver trustworthy results, building scalable ML systems for cMMM and turning ideas into production-ready solutions.

You will mentor engineers, implement probabilistic techniques, and contribute to the productionization of ML workflows.

Qualifications

• PhD or equivalent experience in CS/Engineering/Math.
• 10+ years of industry experience in ML engineering and 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 (Python, Go, Java, C++).

Responsibilities

• Drive ML project initiatives from concept to production delivery.
• Implement probabilistic techniques into reusable statistical libraries.
• Build and maintain ML systems powering HausHaus products (cMMM).
• Review code and designs of teammates and provide feedback.
• Lead and collaborate with engineering and cross-functional teams to ship end-to-end systems.
• Lead AI workflows for ML pipelines including model validation.
• Mentor ML engineers and raise the ML bar across the org.

Skills

Problem solving

Critical thinking

Writing production code

Cross-functional collaboration

Python

Go

Java

C++

Machine learning engineering

Education

PhD or equivalent in CS/Engineering/Math

Tools

MLFlow

Job description

HausHaus is seeking a senior ML Engineer to drive high-impact projects in advanced marketing planning, analysis, and optimization. You will collaborate with applied scientists, data scientists, and engineers to deliver trustworthy results, building scalable ML systems for cMMM and turning ideas into production-ready solutions.

You will mentor engineers, implement probabilistic techniques, and contribute to the productionization of ML workflows.