Senior Machine Learning Engineer

Position Overview

The work at Autodesk profoundly impacts global innovation, providing software tools for architecture, engineering, manufacturing, and entertainment. As a Senior Machine Learning Engineer at Autodesk Research, you will collaborate with world-class researchers and engineers to develop cutting-edge ML-powered product features, helping customers design and build a better world.

This role is ideal for a passionate software engineer eager to solve complex problems and build innovative solutions. You will specifically focus on implementing generative AI features within Autodesk products, working closely with AI researchers.

You will report to a research manager within the Autodesk Model Delivery team in Autodesk Research. This is a global team with locations in London, San Francisco, Vancouver, Toronto, Montreal, and various remote setups. We support in-person, hybrid, and remote work arrangements, provided you are within commuting distance to one of our offices.

Responsibilities

• Collaborate on research and product intersection projects within a diverse, global team.
• Develop, finetune, and optimize foundation models (LLMs, diffusion, multimodal) on large-scale datasets for CAD/design.
• Develop new or improve existing ML models used in CAD software.
• Process data, analyze feature extractions, and evaluate model behaviors.
• Design solutions based on error analysis and model performance evaluation.
• Present results to collaborators, stakeholders, and leadership across research and engineering.
• Review relevant AI/ML literature to identify emerging methods, technologies, and best practices.
• Partner with research teams to transition cutting-edge models into production systems.
• Monitor and improve model performance in production environments.

Minimum Qualifications

• BSc or MSc in Computer Science or related fields.
• 3+ years of deep learning model development and deployment in production.
• Proficiency in modern deep learning techniques (architectures, regularization, loss functions, optimization) and frameworks (PyTorch, Lightning, Ray).
• Experience with version control, reproducibility, and writing reusable, testable code.
• Experience with data modeling, architecture, and processing, including 2D and 3D geometry.
• Experience with cloud services and architectures (AWS, Azure, GCP).
• Excellent written documentation skills for code, architectures, and experiments.

Preferred Qualifications

• Proficiency with foundation models (LLMs, diffusion models, multimodal models like CLIP, BLIP), including pretraining and post-training.
• Experience with distributed training frameworks (DDP, FSDP, DeepSpeed, Megatron).
• Experience optimizing inference performance and latency for production.
• Experience working across research and engineering to productionize cutting-edge research.
• Knowledge of design, manufacturing, AEC, or media & entertainment industries.
• Experience with Autodesk or similar products (CAD, CAE, CAM).
• Contributions to open-source ML projects or published research in top-tier venues.

Key skills/competency

• Machine Learning Engineering
• Deep Learning
• Generative AI
• Foundation Models
• PyTorch
• Cloud Services (AWS, Azure, GCP)
• Production Deployment
• Data Processing
• Model Optimization
• Research Collaboration