Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture

Autodesk is a company that creates software tools for making buildings, machines, and movies, influencing creative problem-solving globally. They are seeking a Senior Principal ML Engineer to define and drive the technical strategy for large-scale machine learning platforms and systems, focusing on multi-year architecture and cross-team engineering standards.

Responsibilities:

• Define and lead technical strategy for a domain or large-scale platform supporting machine learning systems
• Drive architecture decisions across teams for scalable training, data, evaluation, deployment, observability, and reliability systems
• Lead multi-team initiatives with far-reaching technical impact across a function, platform, or division
• Define technical direction for data pipelines that support large-scale structured and semi-structured technical datasets
• Set standards for data lineage, provenance, governance, and responsible data usage in ML systems
• Lead architecture for distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
• Define scalable approaches for model deployment, inference services, monitoring, and observability for production ML systems
• Influence platform direction for ML-ready representations of geometry, graph, hierarchical, or multimodal data
• Influence standards for engineering quality, architecture, resiliency, risk management, and operational excellence
• Identify long-term technical and operational risks and guide investment decisions that future-proof platform capabilities
• Serve as a technical authority and trusted advisor to engineering leaders, senior engineers, and cross-functional stakeholders
• Resolve complex cross-team technical problems by framing options, aligning stakeholders, and driving execution
• Champion engineering practices that improve service quality, release readiness, monitoring, incident response, and maintainability
• Mentor senior engineers and help build the next level of technical leadership within the organization
• Clearly articulate the business rationale for technical investments and ensure alignment with broader organizational goals

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience
• At least 8 years of industry experience in software engineering, ML platform architecture, distributed systems, or related domains, including experience driving architecture, cross-team technical direction, and large-scale platform outcomes
• Significant experience in software architecture, distributed systems, platform engineering, or ML infrastructure at scale
• Deep expertise in one or more critical areas such as distributed training, data platforms, ML platform architecture, model serving, or reliability engineering
• Proven record of leading technical strategy and delivering cross-team outcomes with broad organizational impact
• Strong command of cloud-native architectures, production engineering practices, and large-scale system design
• Demonstrated ability to influence architecture and engineering standards beyond a single team
• Strong executive-level communication and the ability to connect technical direction to business priorities
• Experience setting architecture direction for ML platforms used across multiple teams or organizations
• Experience building or scaling data pipelines for large-scale structured and semi-structured technical datasets
• Experience with data lineage, provenance, governance, and responsible data usage in ML systems
• Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
• Experience with model deployment, inference services, monitoring, and observability for production ML systems
• Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data
• Experience building or scaling foundation model infrastructure and high-throughput data systems
• Experience leading engineering improvements around resiliency, service reviews, fire drills, and risk reduction
• Familiarity with AEC, design technology, BIM/CAD ecosystems, or Autodesk products
• External technical leadership through architecture leadership, speaking, or domain expertise is a plus