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Job Requisition ID #

26WD94805

Senior Principal Machine Learning Engineer, Foundational Models

Position Overview

Autodesk is transforming the Architecture, Engineering, and Construction (AEC) industry by embedding advanced AI and foundation models into cloud-native platforms such as AutoCAD, Revit, Construction Cloud, and Forma.

As a Senior Principal _Machine Learning_ Engineer, you will act as a technical leader and delivery owner for complex, high-impact ML initiatives spanning foundation models, _reinforcement_ learning, data systems, and large-scale ML platforms. You will operate at the intersection of applied research, engineering, and product—setting technical direction while remaining hands-on in the areas of highest complexity and risk.

This role is designed for a senior ML tech lead with a proven track record of owning and delivering ML systems at scale, including training and operating models in large, distributed environments.

**Reporting:** ML Development Manager, AEC Solutions

**Location:** US or Canada (Remote or Hybrid)

Responsibilities

+ **Technical Strategy & Leadership:** Define the long-term technical vision for Generative AI and Foundation _Model_ infrastructure within the AEC Solutions team. Influence architectural decisions across the broader organization.

+ **End-to-End Delivery:** Lead the design, development, and delivery of complex ML systems. Own the full lifecycle from _model_ architecture selection and data strategy to distributed training and production deployment.

+ **Foundation** **_Model_** **Engineering:** Drive the development of large-scale training pipelines. Collaborate with Research Scientists to translate experimental ideas (custom architectures, novel loss functions) into scalable, performant code.

+ **Scalability & Infrastructure:** Architect solutions for distributed training (e.g., FSDP, Megatron-LM, DeepSpeed) on massive compute clusters. Identify and resolve bottlenecks in data processing and _model_ parallelism to maximize training throughput.

+ **Mentorship & Influence:** Mentor Principal and Senior engineers, fostering a culture of technical ownership, rigorous experimentation, and best practices. Act as a technical partner to Product Management and Engineering leadership.

+ **Cross-Functional Collaboration:** Partner effectively with Data Engineering, Platform, and Research teams to integrate large-scale _multimodal_ AEC data ( _3D_ _geometry_ , images, text) into _model_ development workflows.

+ **Operational Excellence:** Establish standards for _model_ evaluation, versioning, monitoring, and MLOps best practices to ensure reproducibility and reliability in a high-stakes production environment.

Minimum Qualifications

+ Master’s or _PhD_ in a field related to AI/ML such as Computer Science, Mathematics, Statistics, Physics, Computational Linguistics, or related disciplines

+ 10+ years of experience in _machine learning_ , AI, or related fields, with a proven track record of technical leadership and hands-on implementation

+ Demonstrated experience mentoring engineers and leading technical projects in cross-functional environments

+ Proven history of leading the delivery of large-scale ML systems from conception to production

+ Expert-level understanding of deep learning architectures (Transformers, Diffusion models) and modern frameworks ( _PyTorch_ is required)

+ Hands-on experience with distributed training frameworks and techniques (e.g., _PyTorch_ Distributed, Ray, DeepSpeed, Megatron, CUDA optimization) in HPC or cloud environments (AWS/Azure)

+ Strong proficiency in Python, with an emphasis on performance profiling, debugging, and writing robust, maintainable production code

+ Excellent ability to translate complex technical concepts into clear insights for executive leadership and cross-functional partners

Preferred Qualifications

+ Experience with large foundation _model_ training in distributed compute environments

+ Experience designing data pipelines for _multimodal_ datasets at the terabyte/petabyte scale (using Spark, Iceberg, etc.)

+ Experience constructing internal developer platforms for ML, utilizing tools like Kubernetes, Slurm, or Metaflow

+ A portfolio demonstrating the successful translation of academic research papers into tangible product features

+ Background in AEC, computational _geometry_ , or experience working with _3D_ data representations (BIM, CAD, meshes, point clouds)

The Ideal Candidate

+ Owns outcomes, not just components

+ Has operated ML systems at real scale, including the messy parts

+ Brings strong technical judgment shaped by production experience

+ Thrives in ambiguous problem spaces and drives clarity

+ Enjoys mentoring senior engineers and shaping technical culture

+ Is motivated by delivering real-world impact at scale

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.

Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers (Careers%20%[email protected]%3E) .