Staff Applied Scientist

Braze
Austin
Workplace: OnsiteFull timeUSD 184,000 - 299,812 annuallyFunction: Research & Scientific (R&D)Experience: 8+ yearsSkills: ["Technical leadership","Communication","Design review","Code review","Mentorship"]

Lead end-to-end machine learning and AI-enabled customer engagement initiatives on Braze’s Predictive and Generative AI team. Own the ML platform that trains, serves, and monitors customer-specific models, guide replatforming and productionization from prototype to deployment, and set engineering quality bars. Collaborate across messaging, analytics, and data platform teams, mentor senior engineers and data scientists, and connect technical decisions to customer and business outcomes.

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FursaFursa
Braze
Braze
3 days ago

Staff Applied Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live

Job Summary

Lead end-to-end machine learning and AI-enabled customer engagement initiatives on Braze’s Predictive and Generative AI team. Own the ML platform that trains, serves, and monitors customer-specific models, guide replatforming and productionization from prototype to deployment, and set engineering quality bars. Collaborate across messaging, analytics, and data platform teams, mentor senior engineers and data scientists, and connect technical decisions to customer and business outcomes.
Location: Austin
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Own the team’s technical vision and quality bar for the ML platform, defining best practices and production readiness.
  • •Identify and drive transformative initiatives across replatforming training/serving, DS-to-production workflows, and retiring legacy infrastructure.
  • •Build and ship complex ML initiatives at high velocity, including distributed training/serving and model lifecycle management.
  • •Drive cross-team initiatives across messaging, analytics, and data platform surfaces, maintaining technical relationships.
  • •Mentor senior engineers and data scientists through design/code review and production readiness for ML systems.

Pay and Benefits

Salary: USD 184,000 - 299,812 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionPaid LeaveRetirementLearning BudgetParental LeaveEquityRsus

Key Requirements

  • •8+ years building ML systems in production with hands-on depth across data science, ML engineering, and ML operations.
  • •Designed, trained, and operated predictive models under production load (including supervised/unsupervised learning and neural networks).
  • •Built the pipelines and services that run ML models and shipped ML at production scale with reliability and cost considerations.
  • •Deep experience with distributed systems and designing for scale across high-volume data.
  • •Demonstrated technical leadership by owning direction for cross-team, multi-quarter initiatives while maintaining high personal output.
Experience:8+ yearsMachine learningML operationsPredictive analyticsRecommender systemsCustomer engagementMarketing technology
Skills:Technical leadershipCommunicationDesign reviewCode reviewMentorship
Languages:English
Tech Stack:PyTorchTensorflowPythonRuby on RailsMongoDBRedisKubernetesMLflowRayFeature storesML observability

Company Brief

Braze
Provides a customer engagement platform that helps brands create personalized messaging and lifecycle campaigns across mobile, web, email, and other channels to drive retention, engagement, and revenue.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 100M to 250M
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York, United States
Founded: 2011
WebsiteLinkedIn