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Sr. Engineering Manager, Science Platform

Remote:

Full Remote

Contract:

Full time

Experience:

Expert & Leadership (>10 years)

Work from:

Canada

Offer summary

Qualifications:

3+ years in engineering team management, 10+ years as software or machine learning engineer, Experience building ML products from 0-1, BS/MS/PhD in Computer Science or related field, Bonus: Experience with ML workflows in cloud.

Key responsabilities:

Drive engineering execution within the team
Craft and communicate team vision and roadmap
Collaborate with infrastructure and data platform
Partner with product teams for efficient delivery
Ensure high-quality delivery of model outputs

Haus Information Technology & Services Startup https://www.haus.io/

11 - 50 Employees

See more Haus offers

Job description

About Haus

Haus is a first of its kind decision science platform for the new digital privacy paradigm where data sharing and PII is restricted. Haus uses frontier causal inference based econometric models to run experiments and help brands understand how the actions they take in marketing, pricing and promotions impact the bottom line. Our team is comprised of former product managers, economists and engineers from Google, Netflix, Amazon and Meta who saw how costly it is to support high-quality decision science tooling and incrementality testing. Our mission is to make this technology available to all businesses, where all the heavy lifting of experiment design, data cleaning, and analysis/insights are taken care of for you. Haus is working with well known brands like FanDuel, Sonos, and Hims & Hers, and has seen more than 30x ROI by running experiments and helping brands make more profitable decisions. We are backed by top VCs like Insight Partners, 01 Advisors, Baseline Ventures, and Haystack.

What you'll do

This is a unique opportunity to help us build robust and scalable systems that handle ML and Science workloads at Haus. The Science Platform includes the systems that power the Haus product and are at the heart of what we do.

The ideal candidate is an accomplished engineering leader and an excellent communicator, who has deep experience with scalable distributed systems, and is well-versed with data and machine learning systems/workflows. Please apply if you are a great technologist who enjoys leading from the front, learning new things, and a wide breadth of responsibility.

Responsibilities

Drive engineering execution within the Science Platform team on a regular basis

Craft, communicate, and execute on the team’s vision and roadmap in partnership with our platform PM

Collaborate with core infrastructure and data platform to make sound, first-principle decisions

Partner with product engineering squads to ensure high quality, efficient delivery of model outputs into production

Work closely with scientists and MLEs to create an ergonomic workflow as a paved path that maintains some flexibility

Act as a strong summarizer that is able to make tradeoffs among priorities to ensure consistent, high-quality delivery

Qualifications

3+ years of experience managing a team of engineers delivering data and mac products

10+ years of experience as a software or machine learning engineer

Demonstrated experience building ML products from 0 -> 1

Strong execution skills to keep work on track

A healthy balance between digging into code/architecture and leading through others

A bias towards quantitative measure of progress and performance

Demonstrated experience managing and growing engineers up to and through the staff level

Bonus points

Experienced with ML workflows in a cloud computing environment

Earlier stage startup experience

BS/MS/PhD in Computer Science, Applied Mathematics or a related field

What we offer

Competitive salary and early startup equity

Top of the line health, dental, and vision insurance

401k plan

Unlimited PTO with a 10 day minimum

Provide you with the tools and resources you need to be productive (new laptop, equipment, you name it)

Haus is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.