Staff Machine Learning Engineer, ML Platform
Braze · Austin, TX · 1 mo ago
HybridInformation Technology$184k–$314k/yrFull-time
We need to output HTML fragment with sections: About the role? Actually we have sections: WHAT YOU'LL DO (Responsibilities), WHO YOU ARE (Requirements/Qualifications), WHAT WE OFFER (Benefits), maybe Pay (they gave pay range), Schedule? Not present. Also maybe About Braze (company description) but not required. The instruction: use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Include a section only when posting has real specific content. So we need sections: Responsibilities (WHAT YOU'LL DO), Requirements (WHO YOU ARE) maybe split into Requirements and Qualifications? The posting includes "WHO YOU ARE" with experience etc. Could treat as Requirements. Also Benefits (WHAT WE OFFER). Pay (they gave pay range). Also maybe About Braze? Not required but could be included as "About the role"? Actually "About the role" is not present; we have "WHAT YOU'LL DO" etc. We could include "About Braze" as a section but not required; but we can include if we have content. The instruction: Prefer a few substantive sections over many thin ones. So we could have sections: Responsibilities, Requirements, Benefits, Pay. Possibly also Skills? The WHO YOU ARE includes skills; we could put that under Requirements. We'll not duplicate.
We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, AI recruitment process, etc. Also remove navigation, cookie, legal, duplicated lines. Also remove "BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER" etc. Also remove "OUR AI-POWERED BRAZE RECRUITMENT PROCESS" etc. Also remove "Notice Regarding Automated Employment Decision Tool". Also remove "Please see our Candidate Privacy Policy". Also remove "At Braze, we have found our people..." that's intro fluff but maybe it's part of About Braze? It's generic culture description; could be considered "About Braze" but it's fluff. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The intro paragraph about culture might be considered boilerplate? It's not exactly EEO but it's fluff. However it's part of the job description; maybe we keep as a brief "About Braze" section? But they said prefer few substantive sections over many thin ones. The intro is vague; maybe we can omit it as it's not specific to role. The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. The intro is substantive? It's about company culture; could be considered substantive but it's generic. However we could include as "About Braze" section. But they said use headings like About the role, Responsibilities etc. Not About Braze. But we could still use About the role heading for that intro? The intro is about Braze culture, not role. Might be better to omit to keep focused.
Thus sections:
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Include a section only when posting has real specific content. So we need sections: Responsibilities (WHAT YOU'LL DO), Requirements (WHO YOU ARE) maybe split into Requirements and Qualifications? The posting includes "WHO YOU ARE" with experience etc. Could treat as Requirements. Also Benefits (WHAT WE OFFER). Pay (they gave pay range). Also maybe About Braze? Not required but could be included as "About the role"? Actually "About the role" is not present; we have "WHAT YOU'LL DO" etc. We could include "About Braze" as a section but not required; but we can include if we have content. The instruction: Prefer a few substantive sections over many thin ones. So we could have sections: Responsibilities, Requirements, Benefits, Pay. Possibly also Skills? The WHO YOU ARE includes skills; we could put that under Requirements. We'll not duplicate.
We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, AI recruitment process, etc. Also remove navigation, cookie, legal, duplicated lines. Also remove "BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER" etc. Also remove "OUR AI-POWERED BRAZE RECRUITMENT PROCESS" etc. Also remove "Notice Regarding Automated Employment Decision Tool". Also remove "Please see our Candidate Privacy Policy". Also remove "At Braze, we have found our people..." that's intro fluff but maybe it's part of About Braze? It's generic culture description; could be considered "About Braze" but it's fluff. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The intro paragraph about culture might be considered boilerplate? It's not exactly EEO but it's fluff. However it's part of the job description; maybe we keep as a brief "About Braze" section? But they said prefer few substantive sections over many thin ones. The intro is vague; maybe we can omit it as it's not specific to role. The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. The intro is substantive? It's about company culture; could be considered substantive but it's generic. However we could include as "About Braze" section. But they said use headings like About the role, Responsibilities etc. Not About Braze. But we could still use About the role heading for that intro? The intro is about Braze culture, not role. Might be better to omit to keep focused.
Thus sections:
Responsibilities
with - items from WHAT YOU'LL DO.
Requirements
with - items from WHO YOU ARE.
Benefits
with - items from WHAT WE OFFER.
Pay
with containing pay range and OTE.
We must not include filler like "commensurate with experience". Not present.
We must not include schedule.
Now extract details.
Responsibilities list:
- Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure
- Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely
- Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale
- Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams
- Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists
- Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership
We need to split into list items. Each bullet can be a
- . Some bullets have multiple sentences; we can keep as one
- with the sentences.
Requirements list from WHO YOU ARE:
- 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load
- Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement
- A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
- Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run
- An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making
- Bonus: Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- Bonus: ML platform tooling such as MLflow or another model registry, feature stores, or ML observability
- Bonus: Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
- Bonus: Operating under compliance regimes such as SOX or HIPAA
- Bonus: Customer engagement, personalization, or marketing technology domain experience
We could keep bonuses as separate items but maybe combine under a "Bonus" heading? But we only have h3 headings allowed; we could keep them as list items with "Bonus:" prefix.
Benefits list from WHAT WE OFFER:
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
- A curated in-office employee experience, designed to foster community, team connections, and innovation
- Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
- Employee Resource Groups that provide supportive communities within Braze
- Collaborative, transparent, and fun culture recognized as a Great Place to Work®
We should not include "Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here." That's generic; maybe omit.
Pay section: Provide pay range and OTE.
From posting: "For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company."
We can put that in a
.
We should not include "Your exact offer may vary..." maybe it's okay as it's substantive. Keep.
Now produce HTML fragment:
Responsibilities
- Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure
- Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely
- Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale
- Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams
- Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists
- Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership
Requirements
- 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load
- Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement
- A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
- Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run
- An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making
- Bonus: Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- Bonus: ML platform tooling such as MLflow or another model registry, feature stores, or ML observability
- Bonus: Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
- Bonus: Operating under compliance regimes such as SOX or HIPAA
- Bonus: Customer engagement, personalization, or marketing technology domain experience
Benefits
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
- A curated in-office employee experience, designed to foster community, team connections, and innovation
- Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
- Employee Resource Groups that provide supportive communities within Braze
- Collaborative, transparent, and fun culture recognized as a Great Place to Work®
Pay
For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,
Requirements
with- items from WHO YOU ARE.
Benefits
with- items from WHAT WE OFFER.
Pay
withcontaining pay range and OTE. We must not include filler like "commensurate with experience". Not present. We must not include schedule. Now extract details. Responsibilities list: - Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure - Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely - Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale - Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams - Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists - Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership We need to split into list items. Each bullet can be a
- . Some bullets have multiple sentences; we can keep as one
- with the sentences.
Requirements list from WHO YOU ARE:
- 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load
- Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement
- A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
- Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run
- An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making
- Bonus: Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- Bonus: ML platform tooling such as MLflow or another model registry, feature stores, or ML observability
- Bonus: Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
- Bonus: Operating under compliance regimes such as SOX or HIPAA
- Bonus: Customer engagement, personalization, or marketing technology domain experience
We could keep bonuses as separate items but maybe combine under a "Bonus" heading? But we only have h3 headings allowed; we could keep them as list items with "Bonus:" prefix.
Benefits list from WHAT WE OFFER:
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
- A curated in-office employee experience, designed to foster community, team connections, and innovation
- Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
- Employee Resource Groups that provide supportive communities within Braze
- Collaborative, transparent, and fun culture recognized as a Great Place to Work®
We should not include "Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here." That's generic; maybe omit.
Pay section: Provide pay range and OTE.
From posting: "For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company."
We can put that in a
. We should not include "Your exact offer may vary..." maybe it's okay as it's substantive. Keep. Now produce HTML fragment:
Responsibilities
- Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure
- Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely
- Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale
- Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams
- Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists
- Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership
Requirements
- 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load
- Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement
- A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
- Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run
- An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making
- Bonus: Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- Bonus: ML platform tooling such as MLflow or another model registry, feature stores, or ML observability
- Bonus: Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
- Bonus: Operating under compliance regimes such as SOX or HIPAA
- Bonus: Customer engagement, personalization, or marketing technology domain experience
Benefits
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
- A curated in-office employee experience, designed to foster community, team connections, and innovation
- Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
- Employee Resource Groups that provide supportive communities within Braze
- Collaborative, transparent, and fun culture recognized as a Great Place to Work®
Pay
For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,
- items from WHAT WE OFFER.