Senior Machine Learning Engineer - Remote

Overview

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.

In Short

• Join our growing Engineering team to help design, improve and scale Braze's self-learning AI platform.
• Implement AI pipelines in production at scale.
• Use robust software engineering best practices.
• Work closely with customers to translate use cases into platform components.
• Apply extensive knowledge of Python for clean, readable, and extendible code.
• Collaborate with teams on product strategy and roadmap.
• Support teams implementing Braze for customer success.
• Work with data science and back-end technologies like SQL and BigQuery.
• Utilize architecture and DevOps tools such as Kubernetes and Terraform.
• Write well-tested, documented, modular code.

Requirements

• Exceptional coding skills with clean, object-oriented code.
• Experience with Python in a product setting (2+ years).
• Experience in data/machine learning ecosystem (1+ year).
• Familiarity with major cloud platforms (GCP, AWS, Azure).
• Experience putting ML models into production.
• General understanding of supervised learning principles is a plus.
• Ability to communicate clearly and persuasively.
• Structured and organized approach to work.
• Proactive in identifying opportunities and risks.
• Curiosity for learning new technologies in data architecture and science.

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 including fertility benefits and equal paid parental leave.
• Professional development supported by formal career pathing and learning platforms.
• Curated in-office employee experience fostering community and innovation.
• Opportunities for community engagement through volunteer programs.
• Employee Resource Groups for supportive communities within Braze.
• Collaborative and fun culture recognized as a Great Place to Work®.