Architect and significantly influence ML training/serving systems and tooling that unlock faster iteration and larger models.
Drive adoption and reliability of ML systems and own a portfolio of initiatives across multiple teams.
Improve efficiency: GPU utilization, training runtime, data loading, feature performance, and serving latency.
Write high-quality design docs; run design reviews; set standards for correctness, reliability, and velocity.
Partner cross-org on shared infra sequencing, requirements, and adoption.
Mentor other engineers and contribute to engineering best practices across the org.

Requirements

9+ years industry experience in Software / ML Infra Engineering.
Strong systems background: distributed systems, data pipelines, service design, performance tuning, and operational excellence.
Demonstrated experience improving ML training/serving reliability at scale.
Can reason deeply about infra tradeoffs that affect modeling velocity and product outcomes.
Ability to lead through influence: drive adoption across teams and build durable interfaces/standards.
Demonstrated impact: leading cross-team technical initiatives and influencing technical direction.
Excellent communication: can explain tradeoffs clearly to both technical and non-technical stakeholders.
Comfortable mentoring other engineers and raising engineering quality through reviews and technical guidance.

Benefits

Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

ML training systemsML serving systemsGPU utilizationdata loadingfeature performanceperformance tuningdistributed systemsdata pipelinesservice designoperational excellence

Soft skills

mentoringcommunicationinfluencecollaborationleadershiptechnical guidancedesign reviewsstandards settingcross-team initiativesexplaining tradeoffs