Autodesk
Senior/Principal Machine Learning Engineer, Generative AI
Autodesk, Manchester, New Hampshire, United States
Senior/Principal Machine Learning Engineer, Generative AI
Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. We are enhancing our applications with cloud-native capabilities, including data at scale, edge computing, AI-based solutions, and advanced 3D modeling and graphics. This innovation is happening across our flagship products—AutoCAD, Revit, and Construction Cloud—and Forma, our new Industry Cloud.
Location: Hybrid work or remote work in Canada or United States. East Coast Preferred.
Responsibilities
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
Drive strategic technical planning across the team—identifying bottlenecks, proposing long-term architectural improvements, and aligning data/ML infrastructure with product goals
Collaborate closely with data engineers, applied scientists, and product teams to integrate large-scale data and related attributes into model development workflows
Perform hands-on development of data preprocessing, feature extraction, and transformation modules optimized for downstream ML model performance
Define and establish best practices for model experimentation, evaluation, and deployment in high-throughput environments
Investigate and apply advanced techniques including self-supervised learning, active learning, and weak supervision to maximize the value of unlabeled data
Own and evolve the model/data feedback loop by monitoring model quality, diagnosing failure modes, and guiding iterative improvements
Mentor and support a team of ML engineers, fostering a culture of engineering excellence, curiosity, and technical ownership
Stay current with advances in generative AI, foundation models, and data-centric AI—translating research into practical, scalable solutions
Minimum Qualifications
A Master's degree (or higher) in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics or a related field
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
Deep understanding of data modelling, system architectures, and processing techniques, including 2D/3D geometric data representations
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
Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development
Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency
Proven ability to translate theoretical concepts into practical solutions and prototype implementations
Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation
Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams
Other Qualifications
Background in Architecture, Engineering, or Construction
Extensive experience in system design for data preparation, hyperparameter selection, acceleration techniques, and optimization methods
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
Familiarity with responsible AI principles, including bias mitigation, explainability, and ethical AI practices
The Ideal Candidate
Is passionate about solving problems for AEC customers (Architecture, Engineering, and Construction) by applying machine learning techniques
Is a strategic thinker, capable of shaping and executing long-term data-driven initiatives that align with business objectives
Is comfortable working in newly forming ambiguous areas where learning, experimentation and adaptability are key skills
Actively contributes to a learning-driven culture, sharing knowledge, mentoring peers, and fostering an environment of continuous growth
Is bold and iterative, unafraid to share ideas, experiment, and fail fast
About Autodesk 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 guides the way we work, connects 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.
Salary transparency Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, a starting base salary is expected to be between $166,600 and $269,500, with offers based on experience and location. In addition to base salaries, compensation may include bonuses, stock grants, and a comprehensive benefits package. For Canada (BC) based roles, a starting base salary is expected to be between $161,300 and $236,500, with similar compensation structure.
Equal Employment Opportunity Autodesk is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with applicable law.
Diversity & Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging
Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site).
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Location: Hybrid work or remote work in Canada or United States. East Coast Preferred.
Responsibilities
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
Drive strategic technical planning across the team—identifying bottlenecks, proposing long-term architectural improvements, and aligning data/ML infrastructure with product goals
Collaborate closely with data engineers, applied scientists, and product teams to integrate large-scale data and related attributes into model development workflows
Perform hands-on development of data preprocessing, feature extraction, and transformation modules optimized for downstream ML model performance
Define and establish best practices for model experimentation, evaluation, and deployment in high-throughput environments
Investigate and apply advanced techniques including self-supervised learning, active learning, and weak supervision to maximize the value of unlabeled data
Own and evolve the model/data feedback loop by monitoring model quality, diagnosing failure modes, and guiding iterative improvements
Mentor and support a team of ML engineers, fostering a culture of engineering excellence, curiosity, and technical ownership
Stay current with advances in generative AI, foundation models, and data-centric AI—translating research into practical, scalable solutions
Minimum Qualifications
A Master's degree (or higher) in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics or a related field
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
Deep understanding of data modelling, system architectures, and processing techniques, including 2D/3D geometric data representations
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
Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development
Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency
Proven ability to translate theoretical concepts into practical solutions and prototype implementations
Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation
Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams
Other Qualifications
Background in Architecture, Engineering, or Construction
Extensive experience in system design for data preparation, hyperparameter selection, acceleration techniques, and optimization methods
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
Familiarity with responsible AI principles, including bias mitigation, explainability, and ethical AI practices
The Ideal Candidate
Is passionate about solving problems for AEC customers (Architecture, Engineering, and Construction) by applying machine learning techniques
Is a strategic thinker, capable of shaping and executing long-term data-driven initiatives that align with business objectives
Is comfortable working in newly forming ambiguous areas where learning, experimentation and adaptability are key skills
Actively contributes to a learning-driven culture, sharing knowledge, mentoring peers, and fostering an environment of continuous growth
Is bold and iterative, unafraid to share ideas, experiment, and fail fast
About Autodesk 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 guides the way we work, connects 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.
Salary transparency Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, a starting base salary is expected to be between $166,600 and $269,500, with offers based on experience and location. In addition to base salaries, compensation may include bonuses, stock grants, and a comprehensive benefits package. For Canada (BC) based roles, a starting base salary is expected to be between $161,300 and $236,500, with similar compensation structure.
Equal Employment Opportunity Autodesk is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with applicable law.
Diversity & Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging
Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site).
#J-18808-Ljbffr