below marketmost similar roles pay hereabove market
This role pays more than
78%
of similar roles. Most pay
$174,250–$242,062
— the blue band above.
At the midpoint, this role pays about
$250k
versus about
$208k
for comparable roles.
Based on 240 similar postings.
Employer
About Autodesk
Autodesk is a global leader in 3D design, engineering, and entertainment software, enabling users to imagine, design, and create a better world.
Autodesk currently has
31 open roles
on FindRole.
Listed pay typically runs
$142,425–$249,260
across 7 roles with salary data.
JOB TITLE: Senior Principal AI/ML Developer
The Senior Principal AI/ML Developer joins the GET Applied AI organization to lead the application of artificial intelligence, machine learning, and advanced analytics across the B2C business. This role involves setting technical and strategic directions for high-impact initiatives, including personalization, recommendation systems, segmentation, forecasting, and churn prediction. You will develop and train cutting-edge machine learning models and algorithms that leverage customer behavior, product engagement, and commerce signals to create personalized experiences. Key responsibilities include establishing engineering standards for MLOps, model deployment, and experimentation while leading a team of data scientists and machine learning engineers. You will utilize skills in data mining, information retrieval, and applied statistical methods to solve complex business problems. The work focuses on building scalable end-to-end ML platforms and pipelines to drive intelligent decision-making.
Define and drive the vision, roadmap, and investment priorities for AI and machine learning capabilities across the B2C business.
Lead a portfolio of complex, cross-functional AI/ML programs from initial strategy through production and business adoption.
Provide leadership, coaching, and career development for Data Scientists and Machine Learning Engineers.
Establish technical direction and engineering standards for model development, experimentation, production deployment, and MLOps.
Design and develop scalable end-to-end ML platforms and pipelines to enable personalization and intelligent decision-making at scale.
Establish robust experimentation and measurement practices to test hypotheses and quantify the incremental impact of models.
Serve as a thought partner to senior leaders to translate ambiguous business problems into actionable data and AI strategies.
Develop narratives that connect model performance and customer behavior to measurable financial outcomes and business impact.
What we're looking for
Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative or technical field.
10+ years of experience in Data Science, Machine Learning, Applied Research, or a related technical discipline.
7+ years of experience with software or machine learning system design and architecture, including launching and operating production systems.
Demonstrated experience leading teams, technical organizations, or major cross-functional programs including setting strategy and driving execution.
Experience developing technical talent through coaching, mentorship, technical leadership, performance management, or people management.
Deep hands-on experience with machine learning, data mining, information retrieval, recommendation systems, and applied statistical methods.
Strong expertise in A/B testing, experimental design, causal reasoning, and measurement.
MS or PhD in Data Science, Statistics, Computer Science, Machine Learning, Engineering, or another quantitative discipline (preferred).
15+ years of experience in machine learning, data science, or related disciplines, ideally in eCommerce or growth (preferred).
5+ years of experience in technical or people leadership, including building high-performing Data Science or Machine Learning Engineering teams (preferred).
Hands-on experience with cloud machine learning platforms such as AWS or Azure and modern MLOps best practices (preferred).
Machine Learning
Robotics
Python
C++
Trajectory Generation
Reinforcement Learning
Imitation Learning
Generative Models
Distributed ML Pipelines
Motion Planning
Embodied AI
Simulation
Production ML Systems