Machine Learning Engineer: 2D & 3D Geometric Data, Generative AI East Coast, United States

Solutions Team.

Location: We support hybrid work or remote work in Canada.

Responsibilities

• Collaborate with other engineers to develop scalable data pipelines and architectures

• Work with large-scale datasets including text and geometric data, to support preprocessing, augmentation, analysis and content understanding

• Write production-quality code for model training, testing, and deployment.Design and execute model experiments, evaluate performance, and iterate based on findings

• Monitor, troubleshoot, and optimize machine learning models to ensure accuracy, efficiency, and low latency

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

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

• Implement agile approaches ensuring flexibility and responsiveness to evolving project needs

Minimum Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, or a related technical field, or equivalent industry experience

• 3-5+ years of hands-on experience in machine learning engineering or a closely related field

• Expertise in training deep neural networks (e.g., CNNs, Transformers), with proficiency in modern deep learning libraries and frameworks such as PyTorch, Lightning, and Ray

• Proven experience scaling machine learning training and data pipelines

• Hands-on experience with Large Language Models (LLMs) and related technologies, including embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems

• Strong background in computational geometry and geometric methods

• Experience in data modeling, architecture, and processing using varied data types, particularly 2D and 3D geometric data representations

• Proficiency with version control, model reproducibility practices, and deployment of machine learning models

• Familiarity with cloud services and architectures, especially AWS (e.g., SageMaker Studio), and ideally Azure

• Strong understanding of fundamental computer science algorithms and their scaling behaviors

• Excellent programming skills in both procedural and data-analytics-oriented languages (e.g., Python)

• Ability to translate theoretical machine learning concepts into practical, scalable solutions and prototype implementations

• Excellent documentation skills, including code, architecture design, and experiment tracking

• Practical experience with hyperparameter tuning, model optimization methods, and acceleration techniques

• Experience with distributed computing platforms such as Apache Spark or Hadoop

• Demonstrated experience developing high-scale, production-grade machine learning algorithms

Preferred Qualifications

• Experience building or working with distributed systems

• Background in the Architecture, Engineering, or Construction (AEC) industry

• Domain knowledge in design, manufacturing, AEC, or media & entertainment industries

• Experience with Autodesk products or similar software tools

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

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