Senior Production ML Engineer — Hybrid, Equity & Flexible PTO

Haus Analytics, Inc.; Seattle (WA); Hybrid; USD 250,000 - 270,000; Full time

Benefits offered by this job

Flexible PTO

Equity

Health insurance

WFH stipend

Office in Seattle

New Parent Leave

Job summary

Haus Analytics, Inc. seeks an experienced ML Engineer to drive high-impact machine learning projects, focusing on cMMM and scalable production systems. The role emphasizes writing production-grade code and collaborating with applied scientists, data scientists, and engineers.

Candidates should have a PhD or equivalent, 10+ years in ML and strong skills in Python/Go/Java/C++. The team values impact, rigor, and scalable design in a fast-paced environment.

Qualifications

• PhD or equivalent experience in CS/Engineering/Math.
• 10+ years of industry experience in ML engineering.
• Experience with cross-functional teams.
• Proficiency in OO languages (Python/Go/Java/C++).
• Experience building production ML systems.
• Experience with exploratory data analysis and experimental design.

Responsibilities

• Lead end-to-end design and delivery of ML solutions.
• Implement probabilistic techniques into reusable libraries.
• Build and maintain ML systems powering Haus product lines (cMMM).
• Review code and designs of teammates.
• Collaborate with engineering and cross-functional partners.
• Design and implement AI workflows for ML pipelines.
• Mentor ML engineers and raise the organization’s ML bar.

Skills

Python

Go

Java

C++

ML engineering

Statistical modeling

Cross-functional collaboration

Education

PhD or equivalent

Tools

MLFlow

Job description

Haus Analytics, Inc. seeks an experienced ML Engineer to drive high-impact machine learning projects, focusing on cMMM and scalable production systems. The role emphasizes writing production-grade code and collaborating with applied scientists, data scientists, and engineers.

Candidates should have a PhD or equivalent, 10+ years in ML and strong skills in Python/Go/Java/C++. The team values impact, rigor, and scalable design in a fast-paced environment.