Principal Machine Learning Developer
4 weeks ago
Job Requisition ID # 24WD79050
Position Overview
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 Media and Entertainment team is hiring a Principal Machine Learning Developer to work on innovative projects that help our customers imagine, design, and make a better world. Reporting to our Senior Software Development Manager, 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 for our content creation software
- Work with research teams and software development teams within a globally distributed setting
- In collaboration with other teams, define software requirements and specifications
- Write clean, scalable, and efficient code (python or C++). Implement new functionalities based on requirements.
- Analyse model errors and design strategies for mitigation
- Conduct model training and hyperparameter tuning
- Handle data processing and preparation at scale
Minimum Qualifications
- 7+ years of experience applying machine learning algorithms and libraries to business problems
- Understanding of fundamental CS algorithms
- Experienced with at least one of the following areas: data modelling, data architecture and network architectures, process automation, batch processing, artefact check-pointing, or similar
- Coding skills in Python and/or C++
- Experience with TensorFlow, PyTorch (or other standard deep learning frameworks)
- University degree in related AI/ML discipline, such as Computer Science, Mathematics, Statistics, Physics (or equivalent experience will be considered)
Preferred Qualifications
- Experience of VFX or Games production
- Cloud experience on AWS, Azure or GCP, ML Ops.
- Background in statistical methods for Machine Learning
- Deep Learning techniques (Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies)
- Diffusion models
- Advanced university degree in a related AI/ML field (PhD or MSc.)
- Experience working on novel concepts and experimenting with new solutions and ideas
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