Machine Learning Engineering Manager, Model Delivery

🕒 February 18

🏄 California – Remote

🏄 California – Remote

💵 $148.5k - $266.2k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

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Autodesk

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1982

📱 Media

Architecture • Engineering • Media

Autodesk is a global leader in software for designers, engineers, builders, and creators. The company provides a comprehensive suite of design and engineering applications including popular products like AutoCAD, Revit, and 3ds Max. Through its Design and Make Platform, Autodesk empowers professionals across various industries to design, visualize, and manage projects efficiently, facilitating innovation and sustainability in architecture, engineering, construction, and manufacturing.

📋 Description

• Lead and grow a team of ML engineers focused on production ML systems • Lead model improvements in response to production issues, product feedback, and new research or platform advancements • Lead production release processes for ML services, including release planning, CI/CD, staged rollouts, and rollback procedures • Build and operate observability and on-call practices for ML features, including monitoring, alerting, dashboards, incident response, and post-incident reviews • Develop and maintain scalable evaluation frameworks, datasets, and automated regression tests to prevent quality regressions • Lead reliability, performance, and cost improvements for inference and serving, including capacity planning and meeting SLAs (latency, throughput, availability) • Partner with researchers, product, and platform teams to define quality bars and production readiness, including Trusted AI requirements • Establish and evolve production standards and governance across ML features (testing, evaluation methodology, release gates, model versioning and lineage) • Partner with platform and product teams to integrate ML capabilities into products

🎯 Requirements

• BS/MS in CS/Engineering or equivalent experience • Experience building and operating software systems, including production ML systems • People leadership experience, or strong technical leadership experience (mentoring, setting direction, driving delivery) • Experience with cloud infrastructure and production observability (AWS, Azure, or GCP) • Experience with CI/CD, reproducible deployments, and operating services in production • Strong written communication and documentation skills

🏖️ Benefits

• Health and financial benefits • Time away and everyday wellness