Staff Machine Learning Engineer, ML Platform

Braze
Austin
Workplace: HybridFull timeUSD 184,000 - 314,000 annuallyFunction: Data Science & Machine LearningExperience: 8+ yearsSkills: ["Communication","Technical leadership","Mentoring","Consensus building","Reliability focus"]

Own the ML platform that powers predictive and generative AI marketing experiences at global scale. Drive production initiatives across distributed training pipelines, model serving, orchestration/queueing, deployment, and cloud identity—ensuring fast, safe, and efficient ML deployment. Set technical direction for training, serving, and observability, lead incident response, raise engineering quality through reviews and readiness practices, and partner across teams to connect technical decisions to customer and business outcomes.

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FursaFursa
Braze
Braze
4 days ago

Staff Machine Learning Engineer, ML Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Own the ML platform that powers predictive and generative AI marketing experiences at global scale. Drive production initiatives across distributed training pipelines, model serving, orchestration/queueing, deployment, and cloud identity—ensuring fast, safe, and efficient ML deployment. Set technical direction for training, serving, and observability, lead incident response, raise engineering quality through reviews and readiness practices, and partner across teams to connect technical decisions to customer and business outcomes.
Location: Austin
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Identify and drive initiatives to improve how ML runs in production, including replatforming orchestration/queueing, overhauling deployment and cloud identity, and retiring legacy infrastructure.
  • •Build and ship complex infrastructure end-to-end, including multi-region model serving fleets and CI/deployment tooling for production safety.
  • •Own the platform technical vision and production quality bar, including model training, deployment, serving, and observability; lead incident response and reliability/cost work.
  • •Drive cross-team initiatives spanning shared infrastructure, deployment tooling, and data systems owned with partner teams.
  • •Raise engineering quality via design/code reviews and production readiness for ML systems, and mentor senior engineers and data scientists.

Pay and Benefits

Salary: USD 184,000 - 314,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionEquity401kPaid LeaveLearning BudgetParental Leave

Key Requirements

  • •8+ years building and operating distributed systems in production with depth in deployment and operations, including CI/CD and infrastructure as code.
  • •Hands-on experience with ML workloads in production, including training pipelines and/or model serving and/or ML platform tooling.
  • •Technical leadership: owning direction for a team and leading multi-quarter initiatives across team boundaries while maintaining high personal output.
  • •Deep working knowledge of Kubernetes and cloud infrastructure, including identity/access management, networking, and cost profiling.
  • •Effective communicator whose designs and recommendations build consensus and drive decisions forward.
Experience:8+ yearsAI/MLDistributed systemsMarketing technology
Skills:CommunicationTechnical leadershipMentoringConsensus buildingReliability focus
Languages:English
Tech Stack:PythonRuby on RailsMongoDBRedisKubernetesCeleryRabbitMQKafkaRayMLflowFeature storesCI/CDInfrastructure as codeAPIsCloud identity and access management

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