Staff Machine Learning Engineer

Responsibilities

• Drive transformative initiatives for ML production infrastructure, including queueing, orchestration, deployment, cloud identity, and infrastructure retirement.
• Build and operate multi-region model-serving fleets, customer-specific model pipelines, and CI and deployment tooling.
• Set the technical vision and production quality bar for model training, deployment, serving, observability, reliability, and cost efficiency.
• Lead incident response for ML systems and coordinate initiatives across shared infrastructure, deployment, and data-platform teams.
• Raise engineering quality through design reviews, code reviews, production readiness practices, and mentoring.
• Connect technical decisions to customer and business outcomes and represent the team’s technical perspective to leadership.

Requirements

• 8+ years building and operating distributed systems in production, including deployment, operations, scalability, reliability, CI/CD, and infrastructure as code.
• Hands-on experience with production ML workloads such as training pipelines, model serving, feature systems, or ML platform tooling.
• Technical leadership experience setting team direction, leading multi-quarter cross-team initiatives, and developing senior engineers while maintaining high personal output.
• Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and cost management.
• Strong verbal and written communication skills with the ability to build consensus and drive decisions.
• Preferred experience with Celery, RabbitMQ, Kafka, Ray, MLflow, model registries, feature stores, ML observability, Python, Ruby on Rails, MongoDB, Redis, SOX, HIPAA, customer engagement, personalization, or marketing technology.

Benefits

• Base pay for U.S. candidates is listed at $184,000-$314,000 per year, with potential equity through restricted stock units; compensation figures excluded from structured benefits.
• Hybrid work arrangement with a curated in-office employee experience.
• Retirement and Employee Stock Purchase Plans, flexible paid time off, and medical, dental, vision, life, and disability coverage.
• Fertility benefits and equal paid parental leave.
• Professional development through career pathing, learning platforms, and a yearly learning stipend.
• Volunteer Week, donation matching, Employee Resource Groups, and a collaborative workplace culture.