Senior/Principal Machine Learning Engineer, Generative AI

Autodesk

The Role

Overview

Lead development of generative AI models and data pipelines for AEC industry.

Key Responsibilities

  • ml pipelines
  • data preprocessing
  • model monitoring
  • generative ai
  • team mentoring
  • tech strategy

Tasks

-Mentor and support a team of ML engineers, fostering a culture of engineering excellence, curiosity, and technical ownership -Investigate and apply advanced techniques including self-supervised learning, active learning, and weak supervision to maximize the value of unlabeled data -Perform hands-on development of data preprocessing, feature extraction, and transformation modules optimized for downstream ML model performance -Architect and implement scalable, production-grade data and ML pipelines that support training and fine-tuning of models -Own and evolve the model/data feedback loop by monitoring model quality, diagnosing failure modes, and guiding iterative improvements -Stay current with advances in generative AI, foundation models, and data-centric AI—translating research into practical, scalable solutions -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 -Set the strategic technical vision for Autodesk’s generative AI capabilities in the AEC domain, influencing both short-term priorities and long-term investments -Collaborate closely with data engineers, applied scientists, and product teams to integrate large-scale data and related attributes into model development workflows -Drive strategic technical planning across the team—identifying bottlenecks, proposing long-term architectural improvements, and aligning data/ML infrastructure with product goals -Define and establish best practices for model experimentation, evaluation, and deployment in high-throughput environments

Requirements

  • spark
  • aws
  • pytorch
  • master's
  • 10+ years
  • distributed computing

What You Bring

-Deep understanding of data modelling, system architectures, and processing techniques, including 2D/3D geometric data representations -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 -Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development -Expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Lightning, Ray) -Is bold and iterative, unafraid to share ideas, experiment, and fail fast -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 -A Master's degree (or higher) in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics or a related field -Background in Architecture, Engineering, or Construction -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 -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 -Familiarity with responsible AI principles, including bias mitigation, explainability, and ethical AI practices -Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams -Extensive experience in system design for data preparation, hyperparameter selection, acceleration techniques, and optimization methods -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 -Is comfortable working in newly forming ambiguous areas where learning, experimentation and adaptability are key skills

The Company

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

Building Design

Construction

Automotive

Building Product Manufacturing

3D Animation

Architecture

Engineering

Construction Professionals

Mechanical Engineering

Mechanical CAD

Thermal Simulation

Electronic Design Automation

Print Circuit Board Design

Mechanical, Electrical, and Plumbing (MEP)

HVAC

Fabrication

Estimation

Infrastructure

Civil Engineering

Genetic Engineering (Life Sciences)