Staff Machine Learning Engineer, ML Platform

Braze

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: San Francisco, CANew York City, NY
Salary: $184,000–$314,000 / yr
Posted: 22 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $232k

This role $249k

$168k most similar roles pay here $330k

This role pays more than 62% of similar roles. Most pay $208,575–$254,750 — the shaded band above. At the midpoint, this role pays about $249k versus about $232k 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 100 open roles on FindRole.

Listed pay typically runs $149,000–$235,000 across 99 roles with salary data.

Most-posted roles

View all roles at Braze

At a glance

TL;DR · Staff Machine Learning Engineer, ML Platform

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Staff Machine Learning Engineer, ML Platform joins the Predictive and Generative AI team to build and operate production-scale machine learning systems. This hands-on role involves owning the platform's technical vision, managing multi-region model serving fleets, and developing distributed pipelines for training hundreds of customer-specific models. The engineer will drive transformative initiatives such as replatforming queueing systems, overhauling deployment infrastructure, and improving production quality through code reviews and mentorship. Key responsibilities include ensuring high-throughput API reliability and optimizing costs across the platform. Required expertise includes building distributed systems, managing Kubernetes and cloud infrastructure, and implementing CI/CD pipelines. The ideal candidate possesses experience with Python, Ruby on Rails, MongoDB, Redis, and tools like MLflow or Kafka. This role solves complex technical challenges in delivering personalized customer experiences through high-scale, automated marketing solutions.

What does a Machine Learning Engineer earn in California?

Median $231150 from 183 postings across 28 companies.

See salary data

Skills

Machine Learning Python Ruby on Rails Kubernetes MongoDB Redis Kafka RabbitMQ Ray MLflow CI/CD Infrastructure as Code Distributed Systems Cloud Infrastructure Feature Stores Model Serving

What you'll do

Drive transformative initiatives to improve how the team runs machine learning in production.
Build and ship complex infrastructure projects from initial design through final production deployment.
Own the technical vision for model training, deployment, serving, and observation.
Manage incident response, reliability, and cost efficiency for large-scale ML systems.
Lead cross-team initiatives by managing technical relationships with partner engineering teams.
Improve engineering quality through code reviews, design reviews, and mentoring senior staff.
Translate technical decisions into clear business outcomes for product and engineering leadership.

What we're looking for

Must have 8+ years of experience building and operating distributed systems in production.
Must have hands-on experience with ML workloads including training pipelines, model serving, or feature systems.
Must be a technical leader capable of owning team direction, leading multi-quarter initiatives, and mentoring senior engineers.
Must possess deep working knowledge of Kubernetes and cloud infrastructure, including identity management and networking.
Must be an effective communicator capable of building consensus and driving decision-making through written and verbal communication.
Experience with queueing and orchestration systems like Celery, RabbitMQ, Kafka, or Ray (preferred).
Experience with ML platform tooling such as MLflow, feature stores, or model registries (preferred).
Experience with Python, Ruby on Rails, MongoDB, Redis, Kubernetes, or compliance regimes like SOX/HIPAA (preferred).

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