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.

WHAT WE OFFER

Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here. More details on benefits plans will be provided if you receive an offer of employment.

From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as:

• Competitive compensation that may include equity
• Retirement and Employee Stock Purchase Plans
• Flexible paid time off
• Comprehensive benefit plans covering medical, dental, vision, life, and disability
• Family services that include fertility benefits and equal paid parental leave
• Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
• A curated in-office employee experience, designed to foster community, team connections, and innovation
• Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
• Employee Resource Groups that provide supportive communities within Braze
• Collaborative, transparent, and fun culture recognized as a Great Place to Work®