Autodesk

Machine Learning Engineering Manager on the Model Delivery team within Autodesk Research, leading production ML engineering across deployment, monitoring, evaluation, reliability, and operational excellence for ML-powered features. This role involves leading and growing a team of ML engineers, improving models based on production issues and feedback, leading production release processes, building observability and on-call practices, developing evaluation frameworks, and leading reliability/performance/cost improvements for inference and serving. The role also partners with researchers, product, and platform teams to define quality bars and production readiness, including Trusted AI requirements, and establishes production standards for ML features.

Machine Learning Engineer with a focus on Generative AI, Computer Vision, and Computer Graphics for the film industry at Autodesk Flow Studio. The role involves designing and implementing ML and GenAI models for visual effects, neural rendering, motion capture, and 3D content generation.

This role is for a Machine Learning Technical Manager at Autodesk, focusing on leading a team to develop and deploy next-generation AI solutions for their VFX platform (Autodesk Flow Studio). The role requires expertise in Computer Vision, Computer Graphics, or Generative AI, with responsibilities including managing a team, defining ML strategy, collaborating with product and engineering, and providing technical oversight for model development and deployment. The ideal candidate has a track record of delivering ML models into production, preferably in media/entertainment, and strong programming skills in Python with ML frameworks.

Principal Software Engineer role focused on developing and shipping AI/ML features within Autodesk's Fusion product. Responsibilities include building production-grade AI features, establishing telemetry and observability for AI services, managing high-availability cloud infrastructure for AI workloads, implementing security and compliance frameworks (SOC2, PRRAF), and integrating AI into complex products. Requires experience taking AI/ML models to production, building AI-powered workflows, and system-level thinking.