Senior System Engineer (Kubernetes, Gitops, AWS)

Job Requisition ID #

25WD85289

Position Overview 

We are looking for an experienced Kubernetes Engineer to join our platform team focusing on AI/ML Platform (AMP). This team builds and maintains central components to fast-track the development new ML/AI models such as model development studio, feature store, model serving, model observability.    

Ideal candidate would have background in Kubernetes based deployments, Cloud infrastructure, DevOps, observability. You will work with a cross-functional team involving MLOps, backend, frontend, software engineering skillsets. As an important contributor to our engineering team, you will help shape the future of our AI/ML capabilities, delivering solutions that inspire value for our organization. You will report to an engineering manager. 

Responsibilities 

• Multi-cloud architecture: Define components which leverages strengths from multiple cloud platforms (e.g., AWS, Azure) to optimize performance, cost, and scalability  

• ML solution deployments: Define infrastructure components to deploy in-house, third party software into Kubernetes

• Monitoring: Define and maintain tech stack to monitor health, cost, performance for our services, infrastructure

• Security: Upgrading the software to fix vulnerabilities, participate SOC2 compliance processes

• CI/CD: Use tools such as Jenkins, spinnaker, ArgoCD to define CI/CD for our infrastructure, services 

• Workflow Automation: Define scripts to automate user onboarding resource creation workflows through infrastructure as code

• Support: Testing/verification of infra changes, investigations for the service outages, production on-call support

• Big Data Management: Collaborate with partner teams to create IAM roles, permissions necessary for the access requests for the datasets 

Minimum Qualifications 

• Educational Background: Bachelor’s degree in Computer Science or equivalent practical experience 

• Over 5 years of hands-on experience in cloud infrastructure management, resource optimizations

• Demonstrated knowledge of Kubernetes based deployments, resource fine tuning, Gitops 

• Comfortable in defining TF modules, helm charts for new components, services

• Experience working with Gitops based deployments (ArgoCD or equivalent)

• Experience in writing CI/CD pipelines for build automations, resource creation, workflow automations

• Knowledge for best practices for cloud resource management in terms cost, availability, security perspective

• Excellent communication and collaboration skills, fostering teamwork and effective information exchange 

• Willingness to contribute to other areas of MLops platform writing backend integrations, data pipelines

Preferred Qualifications 

• Prior experience working on MLOps projects such as deploying model training/inference pipelines, observability tools

• Familiarity with tools and frameworks for monitoring and managing the performance of AI/ML models in production (e.g., MLflow, Kubeflow, TensorBoard) 

• Familiarity with distributed model training/inference pipelines using (KubeRay or equivalent) 

• Prior experience on cloud cost optimizations

• AWS DevOps certifications are plus

• Prior experience as a part of cross-functional team handling Infra/DevOps responsibilities 

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About Autodesk
Welcome 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.

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Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package.

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