Principal Machine Learning Operations Developer for AEC

Overview

Develop scalable ML training pipelines and infrastructure for AEC design data

Key Responsibilities

• distributed training
• model parallelism
• scalable pipelines
• performance analysis
• code development
• data processing

Tasks

-Optimize distributed training systems and develop solutions for model parallelism, checkpointing, and efficient resource management -Support AI researchers by building scalable ML training pipelines and infrastructure for foundation model development -Analyze performance bottlenecks and provide solutions to scaling problems -Implement and maintain robust, testable code that is well documented and easy to understand -Collaborate on projects at the intersection of research and product with a diverse, global team of researchers and engineers -Design efficient data processing workflows for large-scale design datasets and industry-specific file formats

Requirements

• ci/cd
• docker
• kubernetes
• aws
• python
• pytorch

What You Bring

-Familiarity with version control, CI/CD, and deployment pipelines -Excellent communicator who can convey complex technical concepts clearly to diverse audiences -Experience with Autodesk or similar products (Revit, Sketchup, Forma) -Experience with distributed data processing and ML infrastructure (e.g., Apache Spark, Ray, Docker, Kubernetes) -Experience with cloud services and architectures (AWS, Azure, etc.) -Experience with performance optimization, monitoring, and efficiency in large-scale ML systems -A self-starter who can solve problems with minimal supervision while collaborating effectively with a global, remote-first team -Experience scaling ML training and data pipelines for large datasets -Experience with distributed systems for machine learning and deep learning at scale -Excellent written documentation skills to document code, architectures, and experiments -BSc or MSc in Computer Science or related field, or equivalent industry experience -Knowledge of the AEC industry and its specific data processing challenges -Adaptable and creative, comfortable building new infrastructure or working within existing codebases -Strong knowledge of ML infrastructure and model parallelism techniques, including frameworks like PyTorch, Lightning, Megatron, DeepSpeed, and FSDPProficiency in Python and strong software engineering practices -Experience with AEC data formats (e.g., BIM models, IFC files, CAD files, Drawing Sets) -Thrives in ambiguous, rapidly evolving areas where learning and flexibility are essential

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About Autodesk

-Pioneered software for 2D and 3D design, revolutionizing industries. -Known for products like AutoCAD, it reshaped architecture, engineering, and manufacturing workflows. -Empowering creators in fields from construction to digital media, enabling more innovative designs. -Develops tools used in iconic projects, from skyscrapers to blockbuster movies. -Pushes the boundaries of design technology, leading the way in artificial intelligence and automation. -Software is a cornerstone in diverse sectors, from industrial to infrastructure, energy, and entertainment. -Cloud-based solutions streamline design processes and foster real-time collaboration across industries. -A leader in 3D design software, with solutions powering projects in every corner of the globe. -Committed to shaping the future of digital design, bringing complex visions to life.

Sector Specialisms