Software Engineer II, Machine Learning

At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization. To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success. Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you. 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$104,400 - CA$176,040/year, with an expected On Target Earnings (OTE) between CA$116,000 - CA$195,600/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, Braze offers a comprehensive Total Rewards package that includes, among other things, equity grants of restric ... (truncated, view full listing at source)