Engineer

Summary

Join Braze's growing Engineering team to design, improve, and scale its self-learning AI platform. You will use robust software engineering best practices to build modular components, work with customers to translate use cases, and apply your Python expertise to produce clean, readable code. Collaboration with product strategy teams and support for customer implementation are also key responsibilities. The ideal candidate is an exceptional coder with experience in data architecture and machine learning, possessing strong communication and organizational skills. Braze offers a supportive and professional team environment with mentorship and coaching opportunities. The company is committed to work-life harmony and provides a comprehensive benefits package.

Requirements

• 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

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

Preferred Qualifications

General understanding of supervised learning principles is a plus

Benefits

• 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