Senior Machine Learning Engineer

Autodesk; Montreal (administrative region); On-site; CAD 80,000 - 120,000; Full time

Job summary

Autodesk is hiring a Machine Learning Engineer to join their Emerging Media and Entertainment Technology team in Montreal. This role involves implementing and enhancing ML models while collaborating with a globally distributed team on innovative projects.

The ideal candidate will have a BSc or MSc in a related field and extensive experience in applying machine learning algorithms. You will work on a variety of data use cases to help shape future media and entertainment technology solutions.

Qualifications

• 3-5+ years of experience in machine learning.
• Strong understanding of fundamental CS algorithms.
• Solid background in statistical methods and deep learning.

Responsibilities

• Implement and enhance new ML models and AI techniques.
• Support research by building experimental pipelines.
• Analyze model errors and design strategies for mitigation.

Skills

Data modelling

Machine learning algorithms

Deep Learning techniques

Python coding

Statistical methods for Machine Learning

Education

BSc or MSc in Computer Science, Mathematics, Statistics, Physics

Tools

TensorFlow

PyTorch

Job description

Autodesk makes software for people who make things. If you've ever driven a high-performance car, admired a towering skyscraper, used a smartphone, or watched great science fiction films, chances are you've experienced what millions of Autodesk customers are doing with our software. Autodesk's Emerging Media and Entertainment Technology team is hiring Machine Learning Engineers to work on innovative projects that help our customers imagine, design, and make a better world. Reporting to our Director of Research, you will help us with implementing and improving ML models while applying best practices for AI Research. You'll apply ML methodologies and tools to a wide array of data and use cases, and help shape the future of media and entertainment technology.

Responsibilities

• Implement and enhance new ML models and AI techniques
• Work collaboratively on research projects within a globally distributed team
• Support research through building experimental pipelines and prototypes
• Handle data processing and preparation at scale
• Conduct model training and hyperparameter tuning
• Analyze model errors and design strategies for mitigation
• Collaborate with our Advanced Engineering team to implement AI solutions

Minimum Qualifications

• BSc or MSc in a related AI/ML field such as Computer Science, Mathematics, Statistics, Physics (or similar)
• Understanding of fundamental CS algorithms and their scaling behaviors
• Strong skills in data modelling and data architecture
• Ability to decompose large problems into manageable components and develop clear solutions
• 3-5+ years of experience applying machine learning algorithms and libraries to business problems
• Solid background in statistical methods for Machine Learning (Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, and regression techniques)
• Proficient in Deep Learning techniques (Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies)
• Experience with TensorFlow, PyTorch, and other standard deep learning frameworks
• Coding skills in Python and/or C++
• Excellent documentation skills for code and software architecture
• Demonstrated skills in presenting information visually
• Experience explaining new concepts to different audiences (technical or nontechnical) and demonstrating a learner's mindset

Preferred Qualifications

We appreciate experience with one or more of the following:

• Computational geometry and geometric methods (e.g. shape analysis, signal processing, topology, differential geometry, discrete geometry, functional mapping, geometric deep learning, graph neural networks)
• Diffusion models
• Passion for entertainment and media, skills in the use of creative software
• Expertise in network architectures, process automation, batch processing, artefact check-pointing, resilience management
• Multi-modal deep learning and/or information retrieval
• Natural Language Processing
• Reinforcement Learning
• PhD in a AI/ML related field