Staff Machine Learning Engineer - New York

Haus Analytics, Inc.; New York (NY); On-site; USD 250,000 - 270,000; Full time

Benefits offered by this job

Flexible PTO

Equity

Top-tier health insurance

WFH stipend

Office lunches in hubs

Job summary

Haus Analytics, Inc. is seeking a senior ML engineer to lead high-impact projects in marketing planning, analysis, and optimization using ML, causal inference, and optimization techniques.

You will collaborate with applied scientists, data scientists, data engineers, and other ML engineers to deliver trustworthy results and scalable processes. The role emphasizes solving complex problems, writing production-grade code, and advancing ML in a fast-moving marketing tech environment across multiple

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).

Responsibilities

• Drive initiatives from concept to final product delivery, ensuring end-to-end execution for ML solutions.
• Implement probabilistic techniques into reusable statistical libraries (bootstrapping, tests, ML models).
• Build and maintain ML systems powering Haus product lines (cMMM).
• Review code and designs, providing constructive feedback to teammates.
• Lead and 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).

Skills

Statistical thinking

Cross-functional collaboration

Education

PhD or equivalent in CS/Engineering/Math

Tools

Python

Go

Java

C++

Job description

Location

New York, NY

Employment Type

Full time

Department

Compensation

• $250K – $270K

Salary ranges are determined by role and level, and within the range individual pay is determined by additional factors including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in this job posting reflect the base salary only, and do not include equity or benefits.

About Haus

Haus 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.

Some of our benefits include:

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.