Staff Applied Scientist

Braze
Chicago
Workplace: OnsiteFull timeUSD 184,000 - 299,812 annuallyFunction: Research & Scientific (R&D)Experience: 8+ yearsSkills: ["Communication","Mentorship","Technical leadership","Bias toward action","Collaboration"]

Build and ship end-to-end ML and AI enhanced marketing solutions on the PGAI team. Own the ML platform that powers personalized customer engagement at scale, from model training and lifecycle management to flexible high-throughput prediction APIs. Lead initiatives across data science and production, set technical vision and quality bars, drive design/code/production readiness for ML systems, and mentor senior engineers and data scientists while translating technical decisions into customer and business outcomes.

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FursaFursa
Braze
Braze
3 days ago

Staff Applied Scientist

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Last checked: 1 hour agoStatus: Live

Job Summary

Build and ship end-to-end ML and AI enhanced marketing solutions on the PGAI team. Own the ML platform that powers personalized customer engagement at scale, from model training and lifecycle management to flexible high-throughput prediction APIs. Lead initiatives across data science and production, set technical vision and quality bars, drive design/code/production readiness for ML systems, and mentor senior engineers and data scientists while translating technical decisions into customer and business outcomes.
Location: Chicago
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Identify and drive transformative initiatives across model training/serving, data-to-production pipelines, and infrastructure lifecycle.
  • •Build and ship at high velocity end to end, including distributed model training/serving and model lifecycle management.
  • •Own the team’s technical vision and quality bar, defining best practices and anticipating production issues.
  • •Drive cross-team initiatives spanning messaging, analytics, and the data platform, maintaining technical relationships.
  • •Raise engineering quality through design review, code review, production readiness, and mentoring senior engineers and data scientists.

Pay and Benefits

Salary: USD 184,000 - 299,812 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability401kEquityPaid LeaveLearning BudgetParental LeaveRetirement

Key Requirements

  • •8+ years building ML systems in production with hands-on depth across data science, ML engineering, and ML operations, including designing, training, deploying, and operating models under load.
  • •Designed and shipped predictive models using supervised/unsupervised learning and neural networks (e.g., recommenders) and built the pipelines/services that run them.
  • •Strong distributed systems fundamentals, with experience designing for scale, reliability, and cost.
  • •Technical leadership with ownership of direction and multi-quarter initiatives across team boundaries while maintaining high personal output.
  • •Experience prototyping, refining, and deploying predictive models using frameworks such as PyTorch and TensorFlow.
Experience:8+ years
Skills:CommunicationMentorshipTechnical leadershipBias toward actionCollaboration
Languages:English
Tech Stack:PyTorchTensorflowMLflowRayFeature storesML observabilityPythonRuby on RailsMongoDBRedisKubernetesNeural networksRecommendersDistributed systems

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