Machine Learning Engineer at Autodesk

**Who this is for** This role is for a software engineer passionate about machine learning who wants to collaborate with researchers to build generative AI feat

Work type: onsite

Location: San Francisco, CA, USA

Type: Full-time

Summary

**Who this is for** This role is for a software engineer passionate about machine learning who wants to collaborate with researchers to build generative AI features into global-scale design and engineering software. **Key highlights** You will work in a global, cross-functional environment to bridge the gap between research models and production-ready features, specifically focusing on backend service development and model deployment. **You might be a good fit if you...** - Have hands-on experience training and deploying deep learning models using PyTorch or TensorFlow. - Are proficient in building scalable RESTful backend services using frameworks like FastAPI. - Have familiarity with cloud infrastructure and MLOps practices for model lifecycle management. - Possess strong written communication skills for documenting technical architectures and experimental results.

Job Description

Job Requisition ID #

26WD97077

Position Overview

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world.

As a Machine Learning Engineer at Autodesk Research, you will work side-by-side with world-class researchers and engineers to build new ML-powered product features that help our customers imagine, design, and make a better world. You are a software engineer who is passionate about solving problems and building things. You are excited to collaborate with AI researchers to implement generative AI features in Autodesk products.

You will report to a research manager in the Autodesk Model Delivery team within Autodesk Research. We are a global team located in London, San Francisco, Toronto, and remote locations. For this role, we support in-person, hybrid, and remote work arrangements.

Responsibilities

• Collaborate on projects at the intersection of research and product with a diverse, global team of researchers and engineers

• Write clean, reusable, and well-documented code with proper version control practices

• Explore and apply transfer learning strategies to improve model generalization in low-resource settings

• Preprocess large-scale datasets and perform feature extraction and analysis to support model development

• Design solutions based on error analysis and model performance evaluation

• Present results to collaborators, stakeholders and leadership across research and engineering teams

• Develop and maintain FastAPI-based backend services to expose ML model inference to internal tools and Autodesk product teams

• Monitor and improve model performance in production environments

• BSc in Computer Science or related fields

• At least one internship or equivalent project experience involving machine learning model training and deployment

• Hands-on experience developing and deploying deep learning models, including familiarity with model architectures, loss functions, optimization strategies, and regularization techniques

• Proficiency with at least one deep learning framework such as PyTorch or TensorFlow

• Experience building RESTful backend services or APIs (e.g., FastAPI, Flask)

• Familiarity with cloud services and architectures (e.g., AWS, Azure, GCP)

• Experience with version control (Git) and writing reproducible, testable code

• Good written communication skills for documenting code, architectures, and experiments

• Experience with distributed computing or data processing frameworks (e.g., Ray, Spark) for large-scale dataset preparation

• Familiarity with MLOps tooling such as AWS SageMaker, Docker, and Kubernetes for model training and deployment pipelines

• Exposure to 2D or 3D geometry data representations, or experience in CAD/engineering software domains

• Experience with generative AI models, including LLMs, diffusion models, or multimodal models

• Familiarity with cross-domain transfer learning or domain adaptation techniques

• Knowledge of the design, manufacturing, or AEC industries

• Contributions to open-source ML projects or academic research experience

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’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect 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. Ready to shape the world and your future? Join us!

Benefits

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting [https://benefits.autodesk.com/](https://benefits.autodesk.com/)

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $96,000 and $172,425. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

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