Staff Applied Scientist

Braze

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TXNew York, NY
Salary
$184,000–$299,812 / yr
Posted
40 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $213k
This role $242k
$134k $318k
below market most similar roles pay here above market

This role pays more than 77% of similar roles. Most pay $184,960–$240,437 — the blue band above. At the midpoint, this role pays about $242k versus about $213k for comparable roles.

Based on 240 similar postings.

Employer

About Braze

Braze is a leading cloud-based customer engagement platform that enables brands to foster human connection with consumers through interactive, real-time, cross-channel marketing.

Braze currently has 105 open roles on FindRole.

Listed pay typically runs $149,000–$235,000 across 104 roles with salary data.

Most-posted roles

View all roles at Braze

At a glance

TL;DR · Staff Applied Scientist

JOB TITLE: Staff Applied Scientist The Staff Applied Scientist joins the Predictive and Generative AI team to deliver personalized customer experiences through machine learning and AI-enhanced marketing solutions. This hands-on delivery role involves leading complex initiatives from prototype to production, including distributed model training, serving, and lifecycle management. You will build the ML platform, manage training pipelines, and develop high-throughput APIs to serve predictions into messaging systems. Key responsibilities include defining the technical vision, mentoring senior engineers, and ensuring production readiness for ML systems. Required expertise includes building production ML systems using PyTorch and Tensorflow, with strong distributed systems fundamentals for scaling billions of data points. Preferred skills include experience with Python, Ruby on Rails, MongoDB, Redis, Kubernetes, and tools like MLflow, Ray, or feature stores within the marketing technology domain.

What does a Applied Scientist earn?

Median $224400 from 38 postings across 10 companies.

See salary data

What you'll do

  • Identify and drive transformative initiatives to replatform model training, serving, and production infrastructure.
  • Build and ship complex ML initiatives from design through production, including distributed model training and lifecycle management.
  • Own the team's technical vision, define best practices, and set the quality bar for the ML platform.
  • Lead technical relationships with messaging, analytics, and data platform teams to ensure seamless solution integration.
  • Raise engineering quality through design reviews, code reviews, and production readiness for ML systems.
  • Mentor senior engineers and data scientists to improve overall team technical proficiency.
  • Connect technical decisions to business outcomes and represent the team's perspective to leadership.

What we're looking for

  • 8+ years of experience building ML systems in production with depth in data science, ML engineering, and ML operations.
  • Experience designing, training, and operating models and pipelines under production load.
  • Proven technical leadership owning team direction, leading multi-quarter initiatives, and mentoring senior engineers.
  • Deep experience prototyping and deploying predictive models using PyTorch or Tensorflow.
  • Strong distributed systems fundamentals for designing at scale, reliability, and cost.
  • Effective verbal and written communication skills to build consensus and drive decision making.
  • Experience with recommender systems, multi-armed bandits, or uplift modeling (preferred).
  • Experience with ML platform tooling, Python, Ruby on Rails, MongoDB, Redis, or Kubernetes (preferred).

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