Intermediate or Senior MLOps Engineer - US Federal
About the positionResponsibilities• Work with multi-functional teams to deliver scalable, secure and reliable solutions. • Build MLOps platform primarily using Kubeflow and other ML ecosystem tools and services for a unified ML Development experience. • Communicate with data scientists, ML engineers, PMs, and architects in requirements elaboration and drive technical solutions. • Own and develop cloud-based services from end to end including infrastructure as code. • Design and build software solutions for efficient organization, storage, and retrieval of data to enable substantial scale.• Build systems and dashboards to monitor service & ML health. • Lead in architecture reviews, code reviews, and technology evaluation. • Research, evaluate, prototype, and drive adoption of new ML tools with reliability and scale in mind. Requirements• 5 or more years of proven industry experience. • Bachelor's and/or Master's degree in Computer Science or Computer Engineering. • Experience in building web applications and microservices and API design. • Professional experience in cloud programming preferably in Python or Go.• Experience with running and maintaining Databricks, Sagemaker, & Apache Spark as a service. • Experience in supporting large Kubernetes networks in production. • Design, implement, and maintain robust MLOps services for deploying, monitoring, and scaling machine learning development and data engineering primarily with Kubeflow. • Troubleshoot and resolve performance bottlenecks, system outages, and other operational issues in collaboration with the ML engineering teams. • Optimize public cloud-based infrastructure (AWS, GCP) to support the computational requirements of machine learning workloads.• Implement and manage CI/CD workflows to automate testing, integration, and delivery of machine learning components. • Ensure the security and compliance of machine learning platforms, implementing best practices for encryption, data protection, and access controls. Nice-to-haves• 8 or more years of validated industry experience forSenior Software Engineer role. • Experience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large scale data lakes.• Experience of data and/or ML systems with ability to think across layers of the stack. • Experience in leading or mentoring other team members. Benefits• Workday Bonus Plan or role-specific commission/bonus. • Annual refresh stock grants. • Flexible work schedule with at least 50% in-office time each quarter. • Comprehensive benefits package. Apply tot his job