Job Requisition ID #25WD92306Job DescriptionPrincipal Machine Learning Developer – AI/ML Platform About AutodeskAutodesk is a global leader in 3D design, engineering, manufacturing, and entertainment software. Our customers use Autodesk software to design and make the physical world that we live in—from complex structures like tall skyscrapers, to strong bridges, to modern cars and even eye-popping movies. The AI/ML Platform helps enable and integrate smart solutions into our software products that improves the design and make process.Position OverviewAutodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking a skilled MLOps Engineer 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 to support platform operations. This role offers a unique opportunity to contribute to the operational success of a strategic AI/ML platform and collaborate with diverse teams to drive innovation in 3D design, engineering, and entertainment softwareResponsibilitiesOperational Efficiency: Drive the operational excellence of our AI/ML Platform by implementing and optimizing MLOps practicesDeployment Automation: Design and implement automated deployment pipelines for machine learning models, ensuring seamless transitions from development to productionScalable Infrastructure: Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processingMonitoring and Logging: Develop and maintain robust monitoring and logging systems to track model performance, system health, and overall platform efficiencyCollaboration with Data Engineers: Work closely with data engineers to ensure efficient data pipelines for model training and validationVersion Control and Model Governance: Implement version control systems for machine learning models and contribute to model governance practicesGovernance and Trust: 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 solutionsSecurity and Compliance: Enforce security best practices and compliance standards in all aspects of MLOps, ensuring data privacy and platform securityContinuous Improvement: Identify opportunities for process automation, optimization, and implement strategies to enhance the overall MLOps lifecycleTroubleshooting and Incident Response: Play a key role in identifying and resolving operational issues, contributing to incident response and system recoveryMinimum QualificationsEducational Background: BS or MS in Computer Science, or related fieldMLOps Experience: 4+ years of hands-on experience in DevOps and MLOps, with a focus on deploying and managing machine learning models in production environmentsInfrastructure as Code (IaC): Proficiency in implementing Infrastructure as Code practices using tools such as Terraform or AnsibleContainerization: Strong expertise in containerization technologies (Docker, Kubernetes) for orchestrating and scaling machine learning workloadsCI/CD: Demonstrated experience in setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines for machine learning projectsScripting and Automation: Strong scripting skills in Python, Bash, or similar languages for automating operational processesMonitoring Tools: Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) for tracking system and model performanceSecurity Awareness: Understanding of security best practices in MLOps, including data encryption, access controls, and compliance standardsCollaboration Skills: Excellent collaboration and communication skills, working effectively with cross-functional teams including data engineers, software developers, and researchersProblem-solving Skills: Proven ability to troubleshoot and resolve complex operational issues in a timely mannerAnalytical advisor role that requires understanding of the theories and concepts of a discipline and the ability to apply best practicesA common career stabilization point (AKA the “full-contributor” level) for Professional rolesRequire knowledge and experience such that the incumbent can understand the full range of relevant principles, practices, and practical applications within their disciplineSolve complex problems of diverse scope by taking a new perspective on existing solutions and applying knowledge of best practices in practical situations.Use data analysis, judgment, and interpretation to select the right course of actionApply creativity in recommending variations in approach“Connect the dots” of assignments to the bigger pictureMay lead projects or key elements within a broader projectMay also have accountability for leading and improving on-going processesBuild effective relationships with more senior practitioners and peers, and build a network of external peersWork independently, with close guidance given at critical pointsMay begin to act as a mentor or resource for colleagues with less experiencePreferred QualificationsCloud Experience: Experience with cloud platforms, especially AWS or Azure, for deploying and managing machine learning infrastructureDatabase Knowledge: Familiarity with databases and data storage solutions commonly used in MLOps, such as SQL, NoSQL, or data lakesMachine Learning Frameworks: Exposure to popular machine learning frameworks (TensorFlow, PyTorch) and their integration into MLOps processesCollaboration Tools: Previous experience with collaboration tools like Git for version control and Jira for project managementAgile Methodology: Familiarity with Agile development methodologies and working in an iterative, collaborative environmentLearn MoreAbout AutodeskWelcome 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!Salary transparencySalary is one part of Autodesk’s competitive compensation package. For Canada-BC based roles, we expect a starting base salary between $131,500 and $180,840. 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.Diversity & BelongingWe take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belongingAre you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site).
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