Principal Machine Learning Developer: AI/ML Platform

Autodesk•Toronto, ON

58d•CA$153,000 - CA$224,400•Remote

About The Position

Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking a skilled Principal MLOps Developer to join our AI/ML Platform team. This role is pivotal in ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML platform used in the development of machine learning and generative AI solutions powering Autodesk’s suite of products and services. You will collaborate with research and product engineering from various domains including design, construction, manufacturing, and media & entertainment to deliver platform capabilities that support the full AI/ML development lifecycle. As a principal-level contributor, you will help build innovative capabilities that enable faster, more secure development and deployment of machine learning and generative AI solutions. You will take ownership of critical platform components, provide architectural direction, and contribute to scalable systems for model training, inference, data processing, deployment automation, monitoring, governance, and operations.

Requirements

Principal-level contributor
Experience in MLOps practices
Experience in designing and engineering software systems and platform services
Experience in designing and implementing automated deployment pipelines for machine learning models and ML artifacts
Experience in developing systems to automate and optimize ML development and operational processes
Experience in designing, implementing, and maintaining scalable infrastructure for model training, inference, data processing, and ML artifact management
Experience in developing tools for building, deploying, and operating ML artifacts in production environments
Experience in automating and orchestrating tasks related to managing large-scale data transformation, data processing, and data stores
Experience in designing and implementing low-latency, scalable prediction and inference services
Experience in developing and maintaining monitoring and logging systems
Experience collaborating with data engineers
Experience collaborating across diverse teams (ML researchers, data engineers, software developers, product managers, software architects, operations teams)
Experience implementing version control systems for machine learning models
Experience contributing to model governance practices
Experience enforcing security best practices and compliance standards
Experience identifying opportunities for process automation and optimization
Experience providing architectural direction

Responsibilities

Drive the operational excellence and technical direction of our AI/ML Platform by implementing and optimizing MLOps practices across the full machine learning development lifecycle
Lead the design and engineering of software systems and platform services for the AI/ML Platform, contributing to scalable, secure, and reliable ML development and operations
Design and implement automated deployment pipelines for machine learning models and ML artifacts, ensuring seamless transitions from development to production
Develop comprehensive systems to automate and optimize laborious ML development and operational processes, integrating them into the platform to streamline operations
Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, data processing, and ML artifact management
Develop tools for building, deploying, and operating ML artifacts in production environments, facilitating a smooth transition from development to deployment
Automate and orchestrate tasks related to managing large-scale data transformation, data processing, and data stores that support model training, validation, deployment, and operations
Design and implement low-latency, scalable prediction and inference services to support the diverse needs of platform users and Autodesk product teams
Develop and maintain robust monitoring and logging systems to track model performance, system health, operational reliability, and overall platform efficiency
Work closely with data engineers to ensure efficient data pipelines for model training, validation, deployment, and ongoing platform operations
Collaborate across diverse teams, including machine learning researchers, data engineers, software developers, product managers, software architects, and operations teams, fostering a collaborative and cohesive work environment
Implement version control systems for machine learning models and contribute to model governance practices
Contribute to the implementation of robust model governance practices, version control systems, and adherence to compliance standards. Uphold data privacy and ethical considerations, fostering trust in our AI/ML solutions
Enforce security best practices and compliance standards in all aspects of MLOps, ensuring data privacy and platform security
Identify opportunities for process automation and optimization, and implement strategies to enhance the overall MLOps lifecycle
Take ownership of critical components of the platform, providing architectural direction and contributing to the overall success of the AI/ML Platform