Position Overview
Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. We're enhancing our applications with cloud native capabilities, including data at scale, edge computing, AI-based solutions, and advanced 3D modeling and graphics. This innovation is happening across our flagship products—AutoCAD, Revit, and Construction Cloud—and Forma, our new Industry Cloud.
 

As a Machine Learning Engineer on the AEC Solutions team, you will join a team of technologists to help build foundation models and generative AI tools for the AEC industry. You will work collaboratively to create and interpret design data that can enhance design and engineering workflows.

Report: You will report to the Manager, Machine Learning Engineering
 

Location: We support hybrid work, and you work near our Boston,
Massachusetts or Toronto, Canada offices.

Responsibilities

• Collaborate with other engineers to develop scalable data pipelines and architectures with a focus on MLOps best practices for large language models (LLMs)

• Support tasks related to data collection, data analysis, content understanding, storage and processing

• Write code for model training, testing, and deployment

• Monitor and troubleshoot machine learning models to ensure accuracy and performance

• Perform requirements analysis, working with team members of different levels and documenting solutions

• Work with large-scale data sets and manage data flow between systems

• Organize and process large batches of text and geometric data

• Communicate your findings through quantitative data analysis and qualitative visuals and insights

Minimum Qualifications

• MS in Machine Learning, Artificial Intelligence, Mathematics, Statistics, Computer Science, or a related field

• 3+ years of experience in machine learning engineering or related field

• ​​Domain expertise in training deep neural nets, such as CNN and transformers and proficiency in least one deep learning framework, for example PyTorch, TensorFlow

• Experience with LLMs and related technologies, including frameworks, embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems

• Experience with data modeling, architecture, and processing using varied data representations including 2D/3D geometry

• Proficient in AWS cloud services and leveraging the SageMaker

• Studio platform for scalable data processing and model development

• Good understanding of fundamental CS algorithms and their scaling behaviors

• Excellent coding skills covering procedural as well as data-analytics oriented languages (such as Python)

• Ability to translate theoretical concepts into practical solutions and prototype implementations

Preferred Qualifications

• Background in Architecture, Engineering, or Construction

• Practical experience in data preparation, hyper-parameter selection; acceleration techniques; and optimization methods

• Experience in parallel distribution of algorithms using platforms such as Spark or Hadoop

• Practical experience in developing high scale machine learning algorithms

 
Ideal Candidate

• You are passionate about solving problems for AEC (Architecture, Engineering, and Construction) customers by applying machine learning techniques

• You are comfortable working in newly forming ambiguous areas where learning and adaptability are key skills

• You easily collaborate with others and are comfortable with minimal direction

• You are constantly striving to learn new technologies and methodologies

• You seek new ways to solve hard problems

• You are unafraid to put your ideas out there and fail fast