Mlops Specialist

About the job MLOps Specialist Education and Work Experience Requirements 5 years of cloud development experience using native services in Azure mainly and AWS secondary Bachelors degree in computer science or similar technical field of study or equivalent practical experience Need to implement Domain Driven Design Microservices APIs and Web Apps Use Cloud design standard methodologies and patterns such as CQRS Event Sourcing Valet Key etc to build highly scalable solutions Able to demonstrate Azure storage and messaging services such as Service Bus Topics Event Hubs Azure Blob and Table Storage Azure SQL and Cosmos DB Integrate Identity management and modern authentication and authorization protocols such as OIDC OAuth 2 0 using Azure Active Directory Azure AD B2C Implement Serverless Functions and Logic Apps for event-driven processes and integrations Use Azure API Management as an API Gateway and perform Able to oversee with the team leader during the generation of technical specifications Able to create and maintenance of programmer documentation If necessary participate in deploying software into the test and development environment Apply standard methodologies and software architecture guidelines Design and develop applications and microservices delivering enterprise-level shared services for the management of private and public clouds Translate cloud-native API commands to tooling formats Work with functional and admin teams to deliver automated workflow solutions with cloud-native tools Advanced development of APIs business rules UI Policies Client Scripts ACLs Workflow Activities etc Facilitate and support the deployment of code through all levels of the SDLC Advise functional and admin teams on design development and overall best practices React quickly to ever-changing market conditions and technological advancements with out of the box solutions that allow our business partners to have the tools that will enable them to reach and exceed our sales goals Manage individual project priorities deadlines and deliverables Work closely with architects and portfolio managers to execute against product roadmaps Design and Develop high-performance scalable and secure cloud-native applications with Python and Microsoft Azure PAAS Services Experience working with and managing work with Jira and other Atlassian tools Extensive experience with Cloud APIs covering software-defined Compute Networking and storage technologies as well as Cloud native automation tools Proven and verifiable history of analyzing business situations and working within a group environment to provide efficient and effective software solutions Participation in the entire software development life cycle driven with agile practices Strong web services experience REST and SOA architectures Experience with Continuous Integration Continuous Deployment Experience with one or more general-purpose programming languages including but not limited to Python Java Script Strong working knowledge designing developing and deploying IaaS and n-tier application hosting on AWS Azure Expertise in Kubernetes and AKS Knowledge of system design and development used within Service Oriented Architecture and web services integration SOAP WSDL JAXWS Proven history of providing technical support during all phases of project delivery This includes but is not limited to development of project estimates solution design review documentation creation and review and peer code reviews Demonstrated experience with service integration using LDAP MS Active Directory ADFS Single Sign-on and web services Designs builds and runs machine learning systems at scale Experience in Microservice based architecture Mandatory Skills Responsible for maintaining the infrastructure that supports the models and algorithms that power the analytical products including Monitoring the performance of these systems Identifying ways to improve their performance Investigating issues when they arise Train models and tune their hyperparameters Analyze the errors of the model and designs strategies to overcome them Deploy models to production Build CI CD pipelines orchestration by GitHub Actions Nexus Airflow Jenkins or similar tools Perform data science model review run the code refactoring and optimization containerization deployment versioning and monitors for quality Perform data science models testing validation and test automation Communicate with a team of data scientists data engineers and architect and document the processes Drive innovation through developing proofs of concept and prototypes to help illustrate approaches to technology and business problems Provide strong technical skills with ability to design architect and get into low-level implementation details Understand business objectives and develop models that help to achieve them along with metrics to track their progress Explore and visualize data to gain an understanding of it and identify differences in data distribution that could affect performance when deploying the model in the real world Proven experience in working with globally distributed agile teams Experience with enterprise DevOps ITIL ITOM processes and tooling implementations Must be adaptable to work in a varied fast paced exciting ever-changing environment Good analytical and problem-solving skills to resolve technical issues Self-starter with desire to understand work and project objectives Excellent organizational analytical written and oral communications skills