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 Braze is seeking a Staff Machine Learning Engineer to join our Predictive and Generative AI (PGAI) team. The team's mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions. We run those solutions as production systems at global scale, from the distributed pipelines that train models for each customer to the high-throughput APIs that serve predictions into our messaging systems across multiple regions. You will own the platform underneath, and you will make deploying, operating, and scaling ML at Braze fast, safe, and efficient. As the Staff Engineer on the team, you will: * Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure * Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely * Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale * Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams * Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists * Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership WHO YOU ARE * 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load * Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement * A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output * Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run * An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making * Bonus: * Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray * ML platform tooling such as MLflow or another model registry, feature stores, or ML observability * Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes) * Operating under compliance regimes such as SOX or HIPAA * Customer engagement, personalization, or marketing technology domain experience For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized 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. #LI-Hybrid 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® ABOUT BRAZE Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.™ Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI™ allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences. The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 “Best of Marketing and Digital Advertising Software Product” in 2025. Braze was also named a 2025 Best Companies To Work For by U.S. News & World Report, a 2025 America’s Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology™ by Great Place To Work®, among other accolades. Braze is also proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore. The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo. BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER At Braze, we strive to create equitable growth and opportunities inside and outside the organization. Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience – regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you. We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we’d love to meet you OUR AI-POWERED BRAZE RECRUITMENT PROCESS At Braze, we’re committed to a fair and transparent candidate experience. To help our recruitment teams focus on what matters most — the person behind each application — we use AI-assisted tools at certain stages of our recruitment process. This includes using AI to analyze the experience, skills and qualifications in your application materials to help with screening and prioritizing candidates. Such screening may amount to a form of solely automated decision-making. We also use AI for administrative support, like scheduling and recording interviews and summarizing interview notes. Our recruiting teams remain responsible for all hiring decisions and are involved throughout the process. Depending on where you are located, you may have certain rights available to you in relation to Braze’s use of AI: * To opt out of AI-assisted review of your application, please click the “Learn More” at the end of the application form below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application. * To exercise other types of rights, such as rights to request further information about how AI is used in our recruitment process, to request a manual review of any decision made or to contest a decision, please contact us at [email protected]. Please contact us at [email protected] with any questions. To find out more about our hiring process, check out this page. Notice Regarding Automated Employment Decision Tool (NYC Local Law 144) Our use of AI during the application review process may include the use of automated employment decision tools. Pursuant to New York City Local Law 144, for roles based in New York City, or if you reside in New York City, you have the right to request an alternative selection process or a reasonable accommodation instead of AI-assisted review. To opt out of AI-assisted review of your application, please click the “Learn More” button below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application. Please submit any other request to our Talent Acquisition team at [email protected] promptly after applying. Summaries of the most recent bias audit results for such tools are available here. Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.

Staff Machine Learning Engineer, ML Platform

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