Braze is looking to design, improve, and scale its self-learning (reinforcement learning) AI platform by hiring engineers to work on data-intensive products and implement AI pipelines in production at scale.
Requirements
- Experience working with at least one major cloud platform (GCP, AWS, Azure, etc)
- Experience putting ML models into production
- 3+ years of experience working with Python in a product setting, including 1+ years in a the data/machine learning ecosystem
- If you have experience and/or like Ruby, this is a differential
- General understanding of supervised learning principles is a plus
- 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
Responsibilities
- Use robust software engineering best practices to design, implement, and improve modular components in a cutting-edge ML product
- Interact with big data, build for scale, and create the infrastructure to leverage all of its latent power.
- Apply 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
- We write well-tested, type-hinted, documented, modular code and use pre-commit hooks, CI/CD, and issue tracking for development
Other
- 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
- LI-Hybrid
- If this sounds familiar, we encourage you to apply, as we’d love to meet you.
