Machine Learning Ops lead
Budget: $15 – $25 USD
FTE, long term job for Machine Learning Ops Lead!
Preferred skills
· Docker practitioner. Demonstrable familiarity with containerized orchestration and virtualization frameworks. Experience with a Kubernetes package manager such as Helm a plus.
· Software engineering (Version Control) and associated best practices
· Advanced programming experience in programming languages used in analytics and data science (e.g. Python, Java, Scala). Comfortable with Linux environments and shell scripting.
· Experience with Cloud-based infrastructures (AWS or Azure) and infrastructure as code (SageMaker, S3, Dynamo, Redshift)
· Understanding of machine learning algorithms
· Design and evaluated approaches to high volume real-time data streams
· Foundation in computer science, system architecture, statistical/quantitative modeling with ability to process large volumes of structured and unstructured data
· Distributed Systems Know-How. Designing, deploying, and troubleshooting distributed systems
· Interface Savvy. Creating and interacting with RESTful HTTPS API's, websockets, and webhooks
· DevOps experience. You enjoy DevOps. You've had some experience monitoring and maintaining mission critical systems and services with uptime requirements.
Preferred skills
· Docker practitioner. Demonstrable familiarity with containerized orchestration and virtualization frameworks. Experience with a Kubernetes package manager such as Helm a plus.
· Software engineering (Version Control) and associated best practices
· Advanced programming experience in programming languages used in analytics and data science (e.g. Python, Java, Scala). Comfortable with Linux environments and shell scripting.
· Experience with Cloud-based infrastructures (AWS or Azure) and infrastructure as code (SageMaker, S3, Dynamo, Redshift)
· Understanding of machine learning algorithms
· Design and evaluated approaches to high volume real-time data streams
· Foundation in computer science, system architecture, statistical/quantitative modeling with ability to process large volumes of structured and unstructured data
· Distributed Systems Know-How. Designing, deploying, and troubleshooting distributed systems
· Interface Savvy. Creating and interacting with RESTful HTTPS API's, websockets, and webhooks
· DevOps experience. You enjoy DevOps. You've had some experience monitoring and maintaining mission critical systems and services with uptime requirements.
Related categories:
Business, Accounting, Human Resources & Legal
Python
Machine Learning (ML)
Docker
Kubernetes