Senior AI/ML Engineer
Tasks
- Apply DevOps and MLOps best practices
- Automate workflows and processes
- Build API endpoints for feature configuration
- Build data pipelines for ML training
- Deploy and monitor ML features in production
- Design and deliver ML-powered features
- Develop ML models and algorithms
- Document code design decisions and operational procedures
- Implement model monitoring and dashboards
- Maintain back office APIs and serving APIs
- Perform unit and integration testing
- Run A/B testing
- Translate business requirements into technical specifications
- Troubleshoot production issues and fix bugs
Perks/Benefits
- Additional paid day off
- Calm subscription
- Employee assistance program
- Flexible working hours
- Paid volunteer days
- Professional education budget
- Stock options
- Work from home
Skills/Tech-stack
A/B | A/B Testing | API Development | B testing | BigQuery | Bigtable | CI/CD | Cloud platform | Dataproc | DevOps | GCS | GKE | Git | Google Cloud | Google Cloud Platform | Grafana | Integration Testing | MLOps | Machine Learning | Microservices | MongoDB | Monitoring | PyTorch | Python | Redis | SaaS | Scikit-learn | Sentry | Software Architecture | Spark | TensorFlow | Unit Testing | VertexAI
Education
N/A
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