Senior Software Engineer, AI/ML Platform
Tasks
- Apply MLOps best practices including reproducibility lineage rollback monitoring governance
- Architect and build ML platform for data processing training evaluation and deployment
- Build model registry feature store and experiment tracking tooling
- Develop developer facing APIs and CLI tools for ML workflows
- Develop reliable workflows across cloud compute Kubernetes and automation
- Implement CI CD lifecycle for continuous retraining testing and model delivery to production
- Integrate ML orchestration and metadata tracking tools with data lake and pipelines
- Mentor junior engineers and influence cloud platform roadmap
- Monitor deployed models post deployment
Perks/Benefits
- 401k match
- Company paid medical/dental/vision insurance
- Employee Assistance Program (EAP)
- Equity options
- Flexible work arrangements
- Parental leave
- Professional development
- Relocation assistance
- Tuition reimbursement
- Unlimited PTO
Skills/Tech-stack
AWS | AWS CDK | Airflow | Azure | CI/CD | Cloud Computing | Containers | Continuous Retraining | Data Lineage | Data Processing | Experiment tracking | Feature Store | GCP | Infrastructure as Code | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Model Deployment | Model Governance | Model Monitoring | Model Registry | Multimodal Data | Multimodal Data Processing | Terraform | Training pipelines | Weights & Biases | “as-code”
Education
N/A
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