ML Platform Engineer [Staff]

About HausHaus 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, Baseline Ventures, and Haystack.
What you'll doThis is a unique opportunity to help us build a robust and scalable foundation for engineering, building and integrating ML, data, identity, caching services to life to support rapid and robust application development. You will be working on the systems that power the Haus product and are at the heart of what we do.
The ideal candidate is somebody who is both a great software engineer 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

• Develop scalable distributed systems that power critical features on the Haus Platform.
• Identify opportunities and lead efforts to consolidate key functionality into reusable, generalized  patterns or services.
• Build efficient solutions on top of Google Cloud Platform using Python and other languages as appropriate.
• Influence and help to operate our entire platform using modern technologies such as Python, Flask, BigQuery, Pub/Sub, EventArc, Apache Beam, etc.
• Contribute heavily to the overall architectural direction at Haus.

Qualifications

• 7+ years of experience as a Software Engineer, with a minimum of 4 years experience building scalable distributed systems incorporating or directly adjacent to data or machine learning.
• Experience building and deploying products that rely on large-scale distributed systems in Python or Go, Scala/Java, or other similar languages:  it makes you uncomfortable deploying something for end-users without thinking about things like performance metrics, monitors and dashboards, graceful degradation and feature flags.
• Demonstrated ability to work in more ambiguous environments:  you are an excellent communicator who can take a high-level goal, work with others to deliver pragmatic, shippable solutions — and then evolve and generalize them.
• Extensive experience with cloud infrastructure (Google Cloud, AWS, etc) and working familiarity with Docker/Kubernetes.
• Experience working with and managing a variety of distributed data systems such as Kafka, Storm, Spark, Clickhouse, Druid, Snowflake, BigQuery, etc.

Bonus points

• Earlier stage startup experience.
• Experience with build systems and infrastructure management tooling like Terraform. 
• Experience with a wide variety of data/ML frameworks and tooling — and can articulate pros and cons from real-world practice.
• 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.