Senior AI/ML Engineer
Tasks
- Apply DevOps and MLOps best practices
- Collaborate with data scientists on feasibility and scalability
- Define and develop API endpoints for configuration and serving
- Deploy and monitor features in production
- Design and deliver ML-powered features
- Develop and implement ML models algorithms and data pipelines
- Document code design decisions and operational procedures
- Implement monitoring systems and dashboards
- Maintain back office APIs models and high performance serving APIs
- Optimize ML model accuracy and efficiency
- Perform unit testing integration testing and A B testing
- Provide L3 support
- Translate business requirements into technical specifications
- Troubleshoot issues and fix bugs
Perks/Benefits
- Calm subscription
- Employee assistance program
- Extra day off each quarter
- Flexible working hours
- Meditation opportunities
- Paid volunteer days
- Professional education budget
- Sports opportunities
- Yoga opportunities
Skills/Tech-stack
A/B | A/B Testing | Agile | B testing | BigQuery | Bigtable | CI/CD | Cloud platform | Dataproc | Deep learning | DevOps | Docker | GCS | GKE | GitLab | Google Cloud | Google Cloud Platform | Grafana | Integration Testing | Jira | Kubernetes | MLOps | Machine Learning | Microservices | MongoDB | PagerDuty | Python | REST APIs | Redis | Sentry | Spark | TensorFlow | Unit Testing | VertexAI
Education
N/A
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