Senior Machine Learning Engineer
Tasks
- Build experiment tracking and model versioning
- Coordinate handoffs from data scientists
- Define integration contracts APIs and schemas for ML services
- Deploy and monitor ML models on AWS
- Design repeatable ML deployment pipelines
- Implement IAM scoping secrets handling and compliance tagging
- Implement ML observability logging metrics dashboards alerting
- Improve model inference performance
- Integrate CI CD for ML services
- Manage model artifacts
- Manage model retraining cadences
- Monitor and optimize AWS spend for ML workloads
- Monitor deployed machine learning services
- Operate Amazon Bedrock backed services
- Provision infrastructure as code
- Reduce incidents through deployment hygiene
- Translate research code into production deployments
Perks/Benefits
- Employer match option
- Flexible spending accounts
- Health insurance
- Long-term disability
- Paid leave
- Paid life insurance
- Pre-tax transit
- Public Service Loan Forgiveness eligible employer
- Retirement Contribution
- Short-term disability
- Summer hours
- Supplemental insurance
Skills/Tech-stack
AWS CDK | AWS Fargate | AWS IAM | AWS Lambda | AWS SAM | Amazon Bedrock | Amazon CloudWatch | Amazon ECS | Amazon S3 | Amazon Web Services | Batching | CI/CD | CloudFormation | Docker | Fargate | Infrastructure as Code | Lambda | ML model monitoring | MLflow | Model Monitoring | Model Serialization | ONNX | ONNX Runtime | PyTorch | Python | Quantization | Terraform | TorchScript | Web Services | Weights and Biases | “as-code”
Education
N/A
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