Principal/Senior Principal Machine Learning Engineer, Generative AI
Autodesk
Design and make software for architecture, engineering, construction, and entertainment industries.
Lead AI/ML development of generative models for AEC tools at Autodesk.
14 days ago ago
C$161,300 - C$269,500
Expert & Leadership (13+ years)
Full Time
Vancouver, British Columbia, Canada
Hybrid
Company Size
11,600 Employees
Service Specialisms
Design
Engineering
Construction
Architecture
Consulting
Product Development
Technology Solutions
Software Development
Sector Specialisms
Building Design
Construction
Automotive
Building Product Manufacturing
3D Animation
Architecture
Engineering
Construction Professionals
Role
Description
self-supervised learning
generative ai
data processing
ml pipelines
model deployment
feedback loop
Investigate and apply advanced techniques including self-supervised learning, active learning, and weak supervision to maximize the value of unlabeled data
Stay current with advances in generative AI, foundation models, and data-centric AI—translating research into practical, scalable solutions
Set the strategic technical vision for Autodesk’s generative AI capabilities in the AEC domain, influencing both short-term priorities and long-term investments
Lead the design and development of intelligent data processing and characterization systems that transform unstructured inputs (e.g., text, images, geometry) into structured, ML-ready formats
Architect and implement scalable, production-grade data and ML pipelines that support training and fine-tuning of models
Collaborate closely with data engineers, applied scientists, and product teams to integrate large-scale data and related attributes into model development workflows
Define and establish best practices for model experimentation, evaluation, and deployment in high-throughput environments
Perform hands-on development of data preprocessing, feature extraction, and transformation modules optimized for downstream ML model performance
Mentor and support a team of ML engineers, fostering a culture of engineering excellence, curiosity, and technical ownership
Own and evolve the model/data feedback loop by monitoring model quality, diagnosing failure modes, and guiding iterative improvements
Drive strategic technical planning across the team—identifying bottlenecks, proposing long-term architectural improvements, and aligning data/ML infrastructure with product goals
Requirements
deep learning
pytorch
aws
master's
10+ years
distributed computing
Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation
Is a strategic thinker, capable of shaping and executing long-term data-driven initiatives that align with business objectives
Is passionate about solving problems for AEC customers (Architecture, Engineering, and Construction) by applying machine learning techniques
Is comfortable working in newly forming ambiguous areas where learning, experimentation and adaptability are key skills
Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency
A Master's degree (or higher) in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics or a related field
Is bold and iterative, unafraid to share ideas, experiment, and fail fast
Expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Lightning, Ray)
Experience with Large Models (LLMs and/or VLMs) and related technologies, including frameworks, embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems, in production settings
Extensive experience in system design for data preparation, hyperparameter selection, acceleration techniques, and optimization methods
Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development
Background in Architecture, Engineering, or Construction
Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams
10+ years of work experience in machine learning, data science, AI, or a related field with a proven track record of technical leadership and hands-on implementation
Proficiency in parallel and distributed computing techniques, with hands-on experience using platforms like Spark, Ray, or similar distributed systems for large-scale data processing and model training
Deep understanding of data modelling, system architectures, and processing techniques, including 2D/3D geometric data representations
Familiarity with responsible AI principles, including bias mitigation, explainability, and ethical AI practices
Proven ability to translate theoretical concepts into practical solutions and prototype implementations
Benefits
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Training + Development
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Interview process
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Visa Sponsorship
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Security clearance
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Company
Overview
Founded in 1982
Year of establishment
Marks the beginning of Autodesk's journey in pioneering design software solutions.
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.
Culture + Values
Innovation: We believe in the power of creativity to push boundaries and change the world.
Collaboration: We work together to create solutions that make a difference.
Customer Success: We are focused on delivering products and services that help our customers succeed.
Sustainability: We are committed to making a positive impact on the planet and communities.
Integrity: We act with honesty and uphold the highest ethical standards.
Inclusion: We embrace diverse perspectives and strive for an environment where everyone belongs.
Environment + Sustainability
2023
Net-zero commitment
Aiming to achieve net-zero carbon status, a critical step in combating climate change.
35%
Carbon emissions reduction
Significant reduction in overall carbon footprint across all emission scopes since 2019.
Designing products that help users make more sustainable decisions, including tools for low-carbon building design.
Aims to advance climate resilience by providing tools to better predict and plan for climate risks.
Promotes circular design principles and helps customers optimize material use and reduce waste.
Inclusion & Diversity
30% Female Workforce
Gender Diversity
As of 2023, 30% of the global workforce identifies as female, highlighting progress in gender diversity across the organization.
25% Leadership Representation
Female Leadership
25% of leadership positions are held by women, indicating strides toward gender parity in executive roles.
2025 Diversity Goal
Leadership Commitment
A strategic initiative to boost representation of underrepresented groups in leadership positions by 2025.
12 Employee Groups
Employee Resource Networks
Twelve employee resource groups are supported, fostering inclusion and community for diverse populations including women, LGBTQ+, and veterans.
Leadership Commitment: Has set a goal to increase representation of underrepresented groups in leadership by 2025.
Inclusive Hiring: Implements inclusive recruitment practices and strives for diverse candidate slates for all roles.