Machine Learning Engineer (Pipeline Developer)

Key Skills

Aartificial intelligence, Algorithms, C++, Data Architecture, Data Modeling, Deep Learning, Machine learning techniques, Python Programming, PyTorch, TensorFlow

Job Description

24WD75344 Machine Learning Engineer (Pipeline Developer)

Position presentation

Autodesk designs software for creators. If you've ever driven a high-performance car, looked at a towering skyscraper, used a smartphone, or seen a great sci-fi movie, chances are you've admired what millions of Autodesk customers are designing. help of our software. Autodesk's Media and Entertainment Emerging Technologies team is recruiting for a Machine Learning Engineer to work on innovative projects that help our customers imagine, design and create a world best. You will report to our Director of Research, and you will help us implement and improve machine learning models while applying AI research best practices. You will apply XML methodologies and tools to a wide range of data and use cases, and help shape the future of media and entertainment technologies.

Responsibilities

• Support research by building pipelines and experimental prototypes

• Support large-scale data processing and preparation

• Analyze model errors and design strategies to mitigate issues

• Implement and improve new machine learning models and AI-related techniques

• Work collaboratively on research projects within an international team.

• Conduct training on models and hyperparameter tuning

• Collaborate with our advanced engineering team to implement artificial intelligence solutions

Minimum requirements

• Bachelor's degree, in a discipline associated with AI/machine learning, such as computer science, mathematics, statistics, physics (or similar field)

• At least 3 years of experience as a pipeline developer for VFX or game production (application of machine learning techniques).

• Understanding of fundamental computer algorithms and their scaling behaviors

• Skilled in data modeling, data architecture and network architectures, process automation, batch processing, artifact verification scoring, resilience management

• Coding skills in Python and/or C++

• Experience with TensorFlow, PyTorch (or other standard deep learning frameworks)

• Documentation skills for code and software architecture

• Autonomy and ability to find solutions and solve problems independently

• Comfort with ambiguity and ability to learn and adapt in newly formed areas

• Proven skills in visual presentation of information

Desired skills

We value experience in one or more of the following areas:

• Computational geometry and geometric methods

• Information on machine learning statistical methods

• Deep learning techniques (network architectures, regularization techniques, learning techniques, objective functions, optimization strategies)

• Delivery models

• Multimodal deep learning or information extraction

• Advanced university degree in a related AI and machine learning field (PhD or MSc)