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