Staff Applied Scientist

Braze
New York, San Francisco
Workplace: OnsiteFull timeUSD 184,000 - 299,812 annuallyFunction: Research & Scientific (R&D)Experience: 8+ yearsSkills: ["Communication","Collaboration","Leadership","Mentorship","Problem-solving"]

Own end-to-end ML and AI-enhanced marketing solutions on Braze’s Predictive and Generative AI team, from model training pipelines to high-throughput prediction APIs powering customer messaging. Lead complex initiatives including distributed training/serving, model lifecycle management, and production-ready platforms for hundreds of customer-specific models. Set the technical vision and quality bar, drive cross-team execution, and mentor senior engineers and data scientists while connecting ML decisions to customer outcomes.

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FursaFursa
Braze
Braze
3 days ago

Staff Applied Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live

Job Summary

Own end-to-end ML and AI-enhanced marketing solutions on Braze’s Predictive and Generative AI team, from model training pipelines to high-throughput prediction APIs powering customer messaging. Lead complex initiatives including distributed training/serving, model lifecycle management, and production-ready platforms for hundreds of customer-specific models. Set the technical vision and quality bar, drive cross-team execution, and mentor senior engineers and data scientists while connecting ML decisions to customer outcomes.
Location: New York, San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Identify and drive transformative initiatives across training/serving, data-to-production workflows, and infrastructure evolution.
  • •Build and ship ML systems at high velocity, including distributed model training/serving and model lifecycle management.
  • •Own technical vision and quality bar by setting direction, defining best practices, and anticipating production issues.
  • •Lead cross-team initiatives spanning messaging, analytics, and data platform surfaces with strong technical relationships.
  • •Improve engineering quality through design/code reviews and production readiness, and mentor senior engineers and data scientists.

Pay and Benefits

Salary: USD 184,000 - 299,812 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisabilityPaid LeaveRetirementEquity GrantsLearning Budget

Key Requirements

  • •8+ years building ML systems in production with hands-on depth across data science, ML engineering, and ML operations.
  • •Experience designing and training supervised and unsupervised predictive models, including neural networks and recommenders.
  • •Hands-on ability building the pipelines and services that run models under production load.
  • •Distributed systems fundamentals for designing scale, reliability, and cost for large-scale data workloads.
  • •Technical leadership with ownership of direction and multi-quarter initiatives across team boundaries.
Experience:8+ yearsPredictive modelingSupervised learningUnsupervised learningNeural networksRecommender systems
Skills:CommunicationCollaborationLeadershipMentorshipProblem-solving
Tech Stack:PyTorchTensorflowMLflowRayMongoDBRedisKubernetesPythonRuby on Rails

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