Staff Machine Learning Engineer - New York

Haus; New York (NY); On-site; USD 180,000 - 320,000; Full time

Benefits offered by this job

Flexible PTO

Equity — startup ownership

Top-tier health, dental, and vision

WFH stipend

Team events and offsites

Free lunch at hub offices

New parent leave

Job summary

Haus, a causal marketing platform, seeks a highly experienced ML Engineer to lead end-to-end ML projects and build scalable systems for cMMM. You will collaborate with applied scientists, data scientists, and engineers to deliver trustworthy results and scalable processes.

The role emphasizes production code, design reviews, and mentorship, with opportunities to influence product, engineering, and science teams across the company.

Qualifications

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field.
• 10+ years of industry experience ideally with a focus on 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 Python, Go, Java or C++ and OO design.

Responsibilities

• Drive initiatives from concept to final product delivery, leading or contributing to design, development, optimization, and productionization of ML solutions.
• Implement probabilistic techniques into reusable statistical libraries, including bootstrapping, statistical tests, and ML models/regressions.
• Build and maintain ML systems powering Haus’ product lines (cMMM).
• Review code and designs of teammates, providing constructive feedback.
• Collaborate with engineering and cross-functional partners to drive system development from ideation to production.
• Design and implement AI workflows for ML pipelines including model validation.
• Mentor ML engineers and raise the organization’s ML bar.

Skills

Machine Learning

Leadership

Code Review

Python

Education

PhD or equivalent

Tools

Python

Go

Java

C++

Job description

About HausHaus is the causal marketing platform top businesses trust to optimize billions in ad spend worldwide. With support from PhD economists, data scientists, and growth experts, Haus’ AI-driven technology translates complex marketing measurement into clear action and outcomes, enabling brands like Dyson, Wayfair, Sonos, Fanduel, SharkNinja, and Intuit to optimize spend, accelerate growth, and make smarter marketing decisions at scale.

The Role

This role will drive high-impact projects for advanced marketing planning, analysis, and optimization at Haus using optimization, machine learning, and causal inference. We are looking for individuals who not only excel in problem solving and critical thinking, but also are interested and proficient in writing production code, turning ideas to scalable systems. This role specifically will work deeply on the cMMM machine learning problem space. The role will be a blend of working with applied scientists, data scientists, data engineers and other MLEs to deliver trustworthy results to our customers while focusing on creating processes that help scale the business.

What you’ll do

• 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.
• Able to 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 (specifically cMMM).
• 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.
• Drive design and implementation of AI (Agentic) workflows for ML pipelines (including model validation).
• Mentor ML engineers and raise the organization’s ML bar.

Qualifications

• PhD or equivalent experience in Computer Science, Engineering, Mathematics or related field.
• 10+ years of industry experience ideally with a focus on 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++).

Bonus Points

• Experience in modern deep learning architectures and probabilistic modeling.
• Expertise in the design and architecture of ML systems and workflows.
• Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, and multi-armed bandits.
• Experience with MLFlow.
• Experience with data science or machine learning approaches in marketing and growth.

What We Offer

We’re a high-performance, low-ego team operating in a fast-moving environment. We care deeply about our customers and expect everyone to take full ownership of their work — this is a place where high expectations fuel even higher growth. If you thrive in ambiguity, take pride in raising the bar, and want to work alongside top-tier peers who challenge and support you, you'll find unmatched opportunities here. If you're looking for predictability or rigid structure or you prefer order-taking to go-getting, we’re probably not the right fit — and that’s okay. We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.

• Flexible PTO - take time when you need it!
• Equity – Startup environment with part-ownership in our successes
• Top of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best
• WFH stipend to support the set up you need to be productive
• Events & Offsites – opportunities to connect and celebrate in real life!
• Free Lunch – Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle)
• New Parent Leave – take time to welcome your newest Hausmate

We value in-person collaboration at Haus and give preference to candidates within commuting distance of our offices in San Francisco, Seattle, and New York City.

Haus is an equal opportunity employer. We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self — we would love to hear from you.