Software Engineer, ML Platform
Mountain View, CA
Haus
Measure incrementality and allocate budget efficiently with Haus - your marketing science & experimentation platform to maximize growth.What you'll doThis is a unique opportunity to help us build a robust and scalable foundation for ML, data, and product development 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 experience with scalable distributed systems, and understands 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, Metaflow, dbt, BigQuery, Pub/Sub, EventArc, Apache Beam, etc.
Qualifications
- 4+ 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 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.
- Experience with cloud infrastructure (Google Cloud, AWS, etc) and working familiarity with Docker/Kubernetes.
- Experience working with 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 data/ML frameworks and tooling.
- 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)
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS BigQuery Causal inference Computer Science dbt Distributed Systems Docker Flask GCP Google Cloud Haystack Java Kafka Kubernetes Machine Learning Mathematics PhD Privacy Python Scala Snowflake Spark Terraform Testing
Perks/benefits: 401(k) matching Career development Competitive pay Equity Gear Health care Insurance Salary bonus Startup environment Unlimited paid time off
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