Principal Machine Learning Engineer – Foundation Models in AEC

6 Minutes ago • 5 Years + • $141,600 PA - $194,700 PA
Research Development

Job Description

Autodesk is seeking a Principal Machine Learning Engineer to lead innovation in the AEC industry by embedding advanced AI into cloud-native platforms. This role involves providing technical leadership at the intersection of applied research and large-scale engineering, partnering with Research Scientists and cross-functional teams. The engineer will advance foundation model research in the AEC domain, focusing on experiment design, distributed training, optimization, and large-scale deployment to ensure efficiency and scalability.
Good To Have:
  • Experience training foundation models on 2D, 3D, or multimodal data at scale
  • Expert-level knowledge of transformers, scaling laws, and distributed training
  • Demonstrated success in optimizing training or deployment pipelines for large models, including familiarity with Ray, DeepSpeed, Megatron, Triton, CUDA, Metaflow/MLflow
  • Familiarity using compute clusters and cloud services for large-scale ML pipelines
  • Experience with multi-GPU and large-scale training in HPC or cloud environments
  • Contributions to PyTorch or large-scale ML frameworks
  • Significant post-graduate research experience, or 5+ years of industry experience
  • Knowledge of AEC-related data modalities (3D geometry, CAD/BIM models, construction text corpus)
Must Have:
  • Collaborate with Research Scientists to translate novel model architectures and experimental ideas into robust, scalable implementations.
  • Develop, optimize, and deploy new ML models and AI techniques at scale.
  • Own the end-to-end training workflow: distributed training, debugging, and performance optimization.
  • Identify and apply best practices in large model training (e.g., parallelization, mixed precision, gradient checkpointing).
  • Drive engineering efforts within a global team of scientists and engineers, ensuring reproducibility and efficiency of experiments.
  • Drive throughput by identifying bottlenecks in training pipelines and implementing improvements.
  • Partner with infrastructure and platform teams to leverage large-scale compute clusters and cloud services.
  • Master’s or PhD in AI/ML related fields.
  • Strong background in deep learning.
  • Strong coding abilities in Python.
  • Hands-on experience with distributed training frameworks.
Perks:
  • Annual cash bonuses
  • Commissions for sales roles
  • Stock grants
  • Comprehensive benefits package
  • Culture of belonging where everyone can thrive

Add these skills to join the top 1% applicants for this job

cross-functional
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autodesk
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Position Overview

Autodesk is driving innovation in the Architecture, Engineering, and Construction (AEC) industry by embedding advanced AI into our next-generation cloud-native platforms. Across industry-defining products like AutoCAD, Revit, Construction Cloud, and Forma, we are harnessing generative AI and foundation models to transform how professionals design, build, and shape the world.

As a Principal Machine Learning Engineer at Autodesk, you will provide technical leadership at the intersection of applied research and large-scale engineering, partnering with Research Scientists and cross-functional teams to accelerate innovation that helps our customers imagine, design, and make a better world. You will help guide a multidisciplinary team of scientists, engineers, and designers working on learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, and construction. In this role, you will take ownership of advancing foundation model research in the AEC domain, leading efforts in experiment design, distributed training, optimization, and large-scale deployment to ensure efficiency and scalability.

You will report to the Machine Learning Manager within the AEC Solutions organization.

Responsibilities

  • Collaborate with Research Scientists to translate novel model architectures and experimental ideas into robust, scalable implementations
  • Develop, optimize, and deploy new ML models and AI techniques at scale
  • Own the end-to-end training workflow: distributed training, debugging, and performance optimization
  • Identify and apply best practices in large model training (e.g., parallelization, mixed precision, gradient checkpointing)
  • Drive engineering efforts within a global team of scientists and engineers, ensuring reproducibility and efficiency of experiments
  • Drive throughput by identifying bottlenecks in training pipelines and implementing improvements
  • Partner with infrastructure and platform teams to leverage large-scale compute clusters and cloud services

Minimum Qualifications

  • Master’s or PhD in a field related to AI/ML such as: Computer Science, Mathematics, Statistics, Physics, Computational Linguistics, Mechanical Engineering, or related disciplines

Strong background in deep learning, including:

  • Implementing custom architectures
  • Optimizing model performance
  • Developing novel loss functions
  • Deploying production-ready solutions
  • Familiarity with transformer-based models across various data modalities. Strong expertise in PyTorch (TensorFlow, JAX also valuable)
  • Strong coding abilities in Python, with emphasis on debugging and performance profiling
  • Hands-on experience with distributed training frameworks (e.g., PyTorch Distributed, DeepSpeed, Megatron-LM, FSDP, Horovod)

Preferred Qualifications

  • Experience training foundation models on 2D, 3D, or multimodal data at scale
  • Expert-level knowledge of transformers, scaling laws, and distributed training
  • Demonstrated success in optimizing training or deployment pipelines for large models, including familiarity with: Ray, DeepSpeed, Megatron, Triton, CUDA, Metaflow/MLflow
  • Familiarity using compute clusters and cloud services for large-scale ML pipelines
  • Experience with multi-GPU and large-scale training in HPC or cloud environments
  • Contributions to PyTorch or large-scale ML frameworks
  • Significant post-graduate research experience, or 5+ years of industry experience, title and level commensurate with experience
  • Knowledge of AEC-related data modalities (3D geometry, CAD/BIM models, construction text corpus) is a strong plus

Ideal Candidate

  • Strong builder mindset with ability to quickly implement and scale research ideas
  • Detail-oriented, with strong debugging instincts and persistence in resolving training failures
  • Passion for enabling cutting-edge research through high-quality engineering
  • Ability to thrive in a fast-paced, collaborative research environment

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. For Canada-BC based roles, we expect a starting base salary between $141,600 and $194,700. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Diversity & Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging

Are you an existing contractor or consultant with Autodesk?

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