Senior/Principal Machine Learning Engineer, Generative AI

Overview

Lead AI/ML for generative models in AEC, design pipelines & data processing

Key Responsibilities

• ai strategy
• model experimentation
• data pipelines
• data processing
• feedback loop
• team mentorship

Tasks

-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 -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 -Define and establish best practices for model experimentation, evaluation, and deployment in high-throughput environments -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 -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 -Investigate and apply advanced techniques including self-supervised learning, active learning, and weak supervision to maximize the value of unlabeled data -Architect and implement scalable, production-grade data and ML pipelines that support training and fine-tuning of models -Perform hands-on development of data preprocessing, feature extraction, and transformation modules optimized for downstream ML model performance

Requirements

• master's
• aws
• sagemaker
• pytorch
• spark
• llm

What You Bring

-Is bold and iterative, unafraid to share ideas, experiment, and fail fast -Is comfortable working in newly forming ambiguous areas where learning, experimentation and adaptability are key skills -A Master's degree (or higher) in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics or a related field -Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development -Proven ability to translate theoretical concepts into practical solutions and prototype implementations -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 -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 -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 -Expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Lightning, Ray) -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 -Familiarity with responsible AI principles, including bias mitigation, explainability, and ethical AI practices -Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation -Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency -Deep understanding of data modelling, system architectures, and processing techniques, including 2D/3D geometric data representations -Background in Architecture, Engineering, or Construction

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About Autodesk

-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.

Sector Specialisms