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Autodesk

AI Research Scientist

Toronto, ON, Canada
AMER - Canada - Ontario - Toronto - University Ave, Canada

Pay: For Canada based roles, we expect a starting base salary between $172,500 and $253,000.
Job type: Full-time
Posting language: English · French
Posted: Sep 28, 2026

Apply About employer

Applications open in a new tab.

Original job description

English section of this bilingual listing.

Job Requisition ID #

26WD101116

L'affichage de poste en français suivra / The French job posting follows.

26WD101116, AI Research Scientist

Position Overview

As a Senior Research Scientist in the AI Lab at Autodesk Research, you will conduct fundamental and applied research on Motion Foundation Models: general-purpose models that can represent, generate, edit, understand, and reason about motion. The work will initially focus on human and object motion and will extend toward multimodal and interactive settings involving text, trajectories, images, video, geometry, robot observations/actions, and other signals.

You will work with scientists, researchers, developers, and designers across generative AI, computer vision, graphics, robotics, simulation, manufacturing, architecture, and construction to develop new model architectures, representations, training methods, datasets, and evaluations for motion intelligence.

Autodesk's AI Lab is active in the wider research community, targeting publications at CVPR, NeurIPS, ICML, ICLR, SIGGRAPH, and other top-tier conferences. We collaborate with leading academic and industry labs, combining the best of an academic research environment with product-guided research. This role will report to a Manager of Research Science in the AI Lab.

Responsibilities

Develop new foundation-model approaches for motion generation, editing, understanding, reasoning, and representation
Drive research end-to-end: identify high-value questions, formulate hypotheses, implement ideas, run experiments, analyze failures, iterate, and communicate conclusions
Investigate motion representations and tokenization, generative modeling, multimodal conditioning and alignment, scalable training, post-training, and model refinement
Design rigorous evaluations, benchmarks, ablations, and diagnostics that reveal genuine model progress and failure modes
Build and modify research code, training pipelines, and data pipelines, using modern AI coding agents where useful while maintaining ownership of correctness, reproducibility, and scientific quality
Work toward ambitious long-term goals while defining concrete milestones and maintaining a high pace of empirical iteration
Collaborate across a global research team and with academic and industry partners; publish at top-tier conferences and help transfer successful ideas into Autodesk technologies

Minimum Qualifications

A Master's or PhD in Computer Science, Machine Learning, Computer Vision, Computer Graphics, Robotics, Mathematics, or a related technical field
A consistent track record of research publications demonstrating experience in applied or fundamental research
Deep knowledge of modern generative or foundation-model methods, such as Transformers, diffusion/flow models, latent-variable models, or related architectures
Strong hands-on ability with PyTorch, JAX, or similar frameworks, including building, modifying, debugging, and scaling research training pipelines; effective use of modern AI-assisted development and coding agents
Excellent experimental judgment: ability to turn ambiguous research questions into testable hypotheses, controlled experiments, useful metrics, and clear conclusions
Demonstrated research ownership, persistence, and execution: a track record of pushing difficult technical problems through repeated experimentation to meaningful results

Preferred Qualifications

Research experience in human motion, character animation, motion capture, embodied agents, robotics, or other spatiotemporal modeling problems
Experience with multimodal or foundation models combining motion with text, images, video, geometry, trajectories, actions, or other modalities
Experience with learned motion representations or tokenization (for example VQ/VAE-style methods) and generative methods such as diffusion, flow matching, or autoregressive modeling
Research experience with large-scale video foundation models, including video generation, spatiotemporal representations, multimodal conditioning, and scalable training
Experience with reinforcement learning, post-training, large-scale/distributed training, dataset construction, or evaluation infrastructure
Knowledge of 3D geometry, computer graphics, geometric deep learning, physically grounded modeling, or Autodesk-relevant domains

----------------------------------------------------------------------------------------------------------------------

26WD101116, Chercheur en intelligence artificielle

Aperçu du poste

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 based roles, we expect a starting base salary between $172,500 and $253,000. 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.

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

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

Read the full bilingual original

Job Requisition ID #

26WD101116

L'affichage de poste en français suivra / The French job posting follows.

26WD101116, AI Research Scientist

Position Overview

Responsibilities

Develop new foundation-model approaches for motion generation, editing, understanding, reasoning, and representation
Drive research end-to-end: identify high-value questions, formulate hypotheses, implement ideas, run experiments, analyze failures, iterate, and communicate conclusions
Investigate motion representations and tokenization, generative modeling, multimodal conditioning and alignment, scalable training, post-training, and model refinement
Design rigorous evaluations, benchmarks, ablations, and diagnostics that reveal genuine model progress and failure modes
Build and modify research code, training pipelines, and data pipelines, using modern AI coding agents where useful while maintaining ownership of correctness, reproducibility, and scientific quality
Work toward ambitious long-term goals while defining concrete milestones and maintaining a high pace of empirical iteration
Collaborate across a global research team and with academic and industry partners; publish at top-tier conferences and help transfer successful ideas into Autodesk technologies

Minimum Qualifications

A Master's or PhD in Computer Science, Machine Learning, Computer Vision, Computer Graphics, Robotics, Mathematics, or a related technical field
A consistent track record of research publications demonstrating experience in applied or fundamental research
Deep knowledge of modern generative or foundation-model methods, such as Transformers, diffusion/flow models, latent-variable models, or related architectures
Strong hands-on ability with PyTorch, JAX, or similar frameworks, including building, modifying, debugging, and scaling research training pipelines; effective use of modern AI-assisted development and coding agents
Excellent experimental judgment: ability to turn ambiguous research questions into testable hypotheses, controlled experiments, useful metrics, and clear conclusions
Demonstrated research ownership, persistence, and execution: a track record of pushing difficult technical problems through repeated experimentation to meaningful results

Preferred Qualifications

Research experience in human motion, character animation, motion capture, embodied agents, robotics, or other spatiotemporal modeling problems
Experience with multimodal or foundation models combining motion with text, images, video, geometry, trajectories, actions, or other modalities
Experience with learned motion representations or tokenization (for example VQ/VAE-style methods) and generative methods such as diffusion, flow matching, or autoregressive modeling
Research experience with large-scale video foundation models, including video generation, spatiotemporal representations, multimodal conditioning, and scalable training
Experience with reinforcement learning, post-training, large-scale/distributed training, dataset construction, or evaluation infrastructure
Knowledge of 3D geometry, computer graphics, geometric deep learning, physically grounded modeling, or Autodesk-relevant domains

----------------------------------------------------------------------------------------------------------------------

26WD101116, Chercheur en intelligence artificielle

Aperçu du poste

En tant que chercheur senior au sein du laboratoire d’IA d’Autodesk Research, vous mènerez des recherches fondamentales et appliquées sur les modèles de base du mouvement (Motion Foundation Models) : des modèles polyvalents capables de représenter, générer, modifier, comprendre et raisonner sur le mouvement. Dans un premier temps, vos travaux porteront principalement sur le mouvement des personnes et des objets, puis s’étendront à des contextes multimodaux et interactifs impliquant du texte, des trajectoires, des images, des vidéos, de la géométrie, des observations et actions de robots, ainsi que d’autres signaux.

Vous travaillerez avec des scientifiques, des chercheurs, des développeurs et des concepteurs issus des domaines de l’IA générative, de la vision par ordinateur, du graphisme, de la robotique, de la simulation, de la fabrication, de l’architecture et de la construction afin de développer de nouvelles architectures de modèles, représentations, méthodes d’entraînement, ensembles de données et évaluations pour l’intelligence du mouvement.

Le laboratoire d’IA d’Autodesk est très actif au sein de la communauté scientifique au sens large et vise des publications lors de conférences de premier plan telles que CVPR, NeurIPS, ICML, ICLR, SIGGRAPH et d’autres. Nous collaborons avec des laboratoires universitaires et industriels de premier plan, alliant le meilleur d’un environnement de recherche universitaire à une recherche orientée produit. Ce poste sera rattaché à un responsable de la recherche scientifique au sein du laboratoire d’IA.

Responsabilités

Développer de nouvelles approches de modèles de base pour la génération, l’édition, la compréhension, le raisonnement et la représentation du mouvement
Mener la recherche de bout en bout : identifier des questions à forte valeur ajoutée, formuler des hypothèses, mettre en œuvre des idées, mener des expériences, analyser les échecs, itérer et communiquer les conclusions
Étudier les représentations et la tokenisation du mouvement, la modélisation générative, le conditionnement et l’alignement multimodaux, l’entraînement évolutif, le post-entraînement et le raffinement des modèles
Concevoir des évaluations, des tests comparatifs, des analyses d’ablation et des diagnostics rigoureux qui révèlent les progrès réels des modèles et leurs modes de défaillance
Développer et modifier le code de recherche, les pipelines d’entraînement et les pipelines de données, en utilisant des agents de codage IA modernes lorsque cela s’avère utile, tout en garantissant l’exactitude, la reproductibilité et la qualité scientifique
Travailler à la réalisation d’objectifs ambitieux à long terme tout en définissant des jalons concrets et en maintenant un rythme soutenu d’itération empirique
Collaborer au sein d’une équipe de recherche internationale et avec des partenaires universitaires et industriels ; publier lors de conférences de premier plan et contribuer à transposer les idées fructueuses dans les technologies d’Autodesk

Qualifications minimales

Un master ou un doctorat en informatique, apprentissage automatique, vision par ordinateur, infographie, robotique, mathématiques ou dans un domaine technique connexe
Un parcours solide de publications de recherche démontrant une expérience en recherche appliquée ou fondamentale
Une connaissance approfondie des méthodes modernes de modèles génératifs ou de base, telles que les Transformers, les modèles de diffusion/flux, les modèles à variables latentes ou les architectures connexes
Solides compétences pratiques avec PyTorch, JAX ou des frameworks similaires, notamment pour la création, la modification, le débogage et la mise à l’échelle de pipelines d’entraînement de recherche ; utilisation efficace des outils modernes de développement et de codage assistés par l’IA
Excellent jugement expérimental : capacité à transformer des questions de recherche ambiguës en hypothèses vérifiables, en expériences contrôlées, en métriques utiles et en conclusions claires
Capacité avérée à prendre en main la recherche, à faire preuve de persévérance et à mener à bien les projets : expérience avérée dans la résolution de problèmes techniques complexes par des expérimentations répétées menant à des résultats significatifs

Qualifications souhaitées

Expérience de recherche dans le domaine du mouvement humain, de l’animation de personnages, de la capture de mouvement, des agents incarnés, de la robotique ou d’autres problèmes de modélisation spatio-temporelle
Expérience avec des modèles multimodaux ou fondamentaux combinant le mouvement avec du texte, des images, de la vidéo, de la géométrie, des trajectoires, des actions ou d’autres modalités
Expérience avec les représentations de mouvement apprises ou la tokenisation (par exemple, les méthodes de type VQ/VAE) et les méthodes génératives telles que la diffusion, l’appariement de flux ou la modélisation autorégressive
Expérience de recherche sur les modèles de base vidéo à grande échelle, notamment la génération vidéo, les représentations spatio-temporelles, le conditionnement multimodal et l’entraînement évolutif
Expérience en apprentissage par renforcement, en post-entraînement, en entraînement à grande échelle/distribué, en construction de jeux de données ou en infrastructure d’évaluation
Connaissances en géométrie 3D, en infographie, en apprentissage profond géométrique, en modélisation fondée sur la physique ou dans des domaines liés à Autodesk

Learn More

About Autodesk

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

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

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

Apply About employer

More about this job

Responsibilities

Develop and research foundation-model approaches for motion generation, understanding, and reasoning. Collaborate with global teams to publish research and integrate successful ideas into Autodesk technologies.

Requirements

Requires a Master's or PhD in a technical field with a strong track record of research publications. Candidates must have deep knowledge of generative models and hands-on experience with frameworks like PyTorch or JAX.

Skills

Generative AI
Computer Vision
Robotics
Machine Learning
PyTorch
JAX
Foundation Models
Motion Intelligence
Transformers
Diffusion Models
Flow Matching
3D Geometry
Computer Graphics
Spatiotemporal Modeling
Reinforcement Learning

Benefits

Annual cash bonuses
Stock grants

Visa sponsorship

Not detected in the job text

Keywords

AI Research Scientist
Motion Foundation Models
Generative AI
Computer Vision
Robotics
Machine Learning
PyTorch
JAX
Transformers
Diffusion Models
Flow Matching
Latent-variable models
3D Geometry
Computer Graphics
Geometric Deep Learning
Spatiotemporal Modeling
Reinforcement Learning
Autodesk Research
CVPR
NeurIPS
ICML
ICLR
SIGGRAPH
Tokenization
Multimodal conditioning
Distributed training
Data pipelines
Research publications
Motion capture
Embodied agents

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