Home Job Postings Machine Learning Solution Architect This topic has replies, 0 voices, and was last updated 5 years ago by youngchoon park. Now Editing “Machine Learning Solution Architect” Name * Password * Email Topic Title (Maximum Length 80) Company * Location Expires at <a href="https://www.johnsoncontrols.com/careers">JCI</a> is the world leader in Building Technology service industry, 23B USD in revenue. https://www.johnsoncontrols.com/careers - https://johnsoncontrols.referrals.selectminds.com/jobs/machine-learning-architect-96723 We are looking for a passionate - Machine Learning & Data Engineering architect in our innovation engineering. please drop me a note you are interested in, youngchoon.park@jci.com Description: What you will do The future is being built today and Johnson Controls is making that future more productive, more secure and more sustainable. We are harnessing the power of cloud, data analytics, the Internet of Things (IoT), and user design thinking to deliver on the promise of intelligent buildings and smart cities that connect communities in ways that make people’s lives and the world better. The Johnson Controls AI Hub’s mission is to infuse AI capabilities into products using a collaborative approach working alongside multiple business units. One of the charters of the hub is to create enablers in order to streamline AI/ML operations right from Data supply strategy to Data discovery to Model training and development to deployment of AI services in the Cloud as well as at the Edge. The AI Hub team is looking to accelerate the creation of tools, services and workflows to aid in the quick and widespread deployment of AI Services on a global scale. We are looking for a talented staff Machine Learning DevOps Engineer/Architect with industry experience to contribute to foundational AI/ML operations engineering with repeatability in mind. The Machine Learning DevOps Engineer/Architect will work with data scientists, platform/data engineers, and domain experts to design machine learning pipelines developing both inbound and outbound data engineering policies. We are looking for someone who has either worked in the capacity of a Data Scientist or worked alongside Data Scientists and understands how to increase production workflows as a next logical step to model experimentation. How you will do it Design and implement end-to-end machine learning pipelines accounting for the variability in data sources and collection policies, data analysis and feature extraction methodologies, modeling frameworks for cloud and edge, and serving infrastructure Use configuration and API management to abstract and automate most manual tasks both pre-modeling and post-deployment Work with data scientists, DevOps, data engineers/SMEs from domain to understand how data availability and quality affects model performance Evaluate open source and proprietary technologies and present recommendations to automate machine learning workflows, model training and versioned experimentation, digital feedback and monitoring What we look for BS in Computer Science/Electrical or Computer Engineering, or has a degree and demonstrated technical abilities in similar areas Comprehensive understanding of AI / ML technologies with experience in using Pytorch, TensorFlow or other frameworks Strong API-first design experience accounting for security, authentication/authorization, logging and usage patterns Deep knowledge in API design standards and best practices like Swagger/OpenAPI 3.0, REST, JSON, Async API execution, API Gateways Hands-on experience with public clouds such as Microsoft Azure (IaaS & PaaS) and its functions, Amazon Web Services, or Google Cloud Platform Infrastructure and networking knowledge: VNet, VPN, DNS, DHCP, Firewalls, Security groups Fluency in SQL, RDBMS, data warehousing concepts and data pipelining Experience with Jenkins, CircleCI, Ansible, Chef, Terraform etc. Strong programming (Python, Java, Javascript, .NET) and scripting (Bash, Shell, PowerShell) skill set Experience working with message brokers, caches, queues, pub/sub concepts API & OAuth understanding on how to validate system is working properly using APIs Container experience using technologies such as Kubernetes, Docker, AKS, Openshift, Service Fabric Knowledgeable in the SCRUM/Agile development methodology 3+ years of experience with Data Science, Cloud and IoT 1+ years of experience with production MLOps Expert in Container technologies like Kubernetes and Docker Expert in building CI/CD pipelines for production Demonstrated ability to work well in a cross-functional team environment Strong spoken and written communication skills Search Jobs Previous Job Searches AI All locations My Profile Create and manage profiles for future opportunities. My Submissions Track your opportunities. I agree to the terms of service Update List
