Machine Learning Engineer IV
Tasks
- Apply evaluation monitoring and deployment practices in production
- Build scalable AI enabled platforms
- Create reusable engineering patterns for scalability
- Design reusable APIs and cloud native services
- Establish CI CD automated testing and deployment standards
- Improve platform performance latency throughput reliability and cost
- Make architecture decisions for scalability and reliability
- Mentor engineers on distributed systems and responsible AI adoption
- Operationalize AI using orchestration and agentic frameworks
Perks/Benefits
- Bonuses
- Disability insurance
- Employee resource groups
- Inclusive culture
- Life insurance
- Paid parental leave
- Paid time off
- Private medical insurance
Skills/Tech-stack
APIs | Amazon Web Services | Automated testing | Cloud Native | Cloud platform | Cloud-native development | Continuous Delivery | Continuous integration | Deployment Automation | Deployment Workflows | Distributed Systems | Full Stack | Full-Stack Development | Google Cloud | Google Cloud Platform | Learning operations | Machine Learning | Machine Learning Operations | Microsoft Azure | Model Evaluation | Model Monitoring | Native Development | Observability | Production Operations | Python | Relational databases | Software Architecture | Stack development | System Architecture | Web Services
Education
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