Staff Applied Scientist

About this role

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 own those solutions end to end, from the models and the flexible training pipelines that build them for each customer to the high-throughput APIs that serve predictions into our messaging systems. You will help set the scope of what is possible for customer engagement at scale, and from that space of possibilities you will lead solutions from prototype to product and build the ML platform that runs them.

As the Staff Engineer on the team, you will:

• Identify and drive the transformative initiatives that change what the team can deliver, whether that's replatforming how we train and serve models, redefining how data science ships to production, 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 initiatives yourself from design through production. Current examples include distributed model training and serving, model lifecycle management, and the pipelines that keep hundreds of customer-specific models healthy across regions

• Own the team's technical vision and quality bar. Set direction across the product portfolio and the ML platform, define best practices, and anticipate problems before they reach production

• Drive initiatives that span teams. Our solutions ship into messaging, analytics, and data platform surfaces, 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 ML systems in production, with hands-on depth across data science, ML engineering, and ML operations. You have designed and trained models yourself, built the pipelines and services that run them, and operated them under production load

• 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 experience prototyping, refining, and deploying predictive models (supervised and unsupervised learning, neural networks, recommenders) with frameworks such as PyTorch and Tensorflow

• Strong distributed systems fundamentals, designing for scale, reliability, and cost on the billions of daily data points our customers generate

• An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making

• Bonus:

• Recommender systems, multi-armed bandits, or uplift modeling in production

• ML platform tooling such as MLflow or another model registry, Ray, feature stores, or ML observability

• Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)

• 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 $299,812/year with an expected On Target Earnings ( OTE ) between $204,000 and $332,400/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.

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 Res

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