WHAT YOU'LL DO
Do you enjoy working on data-intensive products? Come join our growing Engineering team to help design, improve and scale Braze's self-learning (reinforcement learning) AI platform. No toy datasets in notebooks - we're implementing AI pipelines in production at scale! Learn tons about data architecture, data science, and self-learning AI. Work in a team that not only talks-the-talk of development best practices, but walks the walk - unit & integration tests, modular design, CI/CD, pair programming, code reviews - the works.
Responsibilities:
- Use robust software engineering best practices to design, implement, and improve modular components in a cutting-edge ML product
- Work closely with Braze customers to understand, translate and generalize particular use cases to generic platform components
- Apply your extensive knowledge of Python and its ecosystem to produce clean, readable, and extendible code, and coach others on the team in doing the same
- Collaborate with teams responsible for Braze's product strategy and roadmap
- Support teams implementing Braze for customers to ensure their success
- Data Science/Back End: Python (Pyspark, Polars, Ibis), SQL, BigQuery, FastAPI
- Architecture/DevOps: Kubernetes, Airflow, Terraform, GCP
- We write well-tested, type-hinted, documented, modular code and use pre-commit hooks, CI/CD, and issue tracking for development
WHO YOU ARE
- Exceptional coder: you write clean, object-oriented code; you care about good design and terse, testable APIs
- Tinkerer: you regularly explore and learn new technologies and methods, especially in the data architecture and data science domains
- Entrepreneurial: you proactively identify opportunities and risks, work around obstacles, and always seek creative ways to improve processes and outcomes
- Structured and organized: you can structure a plan, align stakeholders, and see it through to execution
- Clear communicator: you are able to express yourself clearly and persuasively, both in writing and speech
- 2+ years of experience working with Python in a product setting, including 1+ years in a the data/machine learning ecosystem
- Experience working with at least one major cloud platform (GCP, AWS, Azure, etc)
- Experience putting ML models into production
- General understanding of supervised learning principles is a plus
For candidates based in Ontario, the pay range at the start of employment for this position is expected to be between CA$153,815 - CA$250,039/year, with an expected On Target Earnings (OTE) between CA$172,000 - CA$279,600/year (including performance-based or variable compensation (bonus or commission). Your particular offer may vary depending on multiple individual factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.