Technical Architect - ML
USA - Remote, United States
R
USD 160K-204K (estimate) Senior-level Full Time
Tasks
- Architect and implement MLOps strategy
- Build container oriented ML platforms
- Collaborate with cross-functional teams to deliver ML solutions
- Conduct architecture reviews and troubleshoot ML system issues
- Design enterprise grade ML and LLM pipelines
- Enable observability and monitoring for ML and LLM systems
- Ensure security governance and compliance for cloud and Kubernetes workloads
- Implement MLOps and LLMOps workflows
- Implement model deployment monitoring and governance standards
- Mentor engineers on MLOps tools and best practices
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | API Gateway | AWS | AWS CloudWatch | AWS Lambda | Amazon EKS | Amazon SageMaker | Apache Airflow | Apache Spark | B testing | BentoML | Blue/green | Blue/green deployments | CI/CD | Canary deployments | CloudWatch | CodeBuild | CodePipeline | Databricks | Docker | Drift Detection | Evaluation metrics | Feature Store | Grafana | Helm | IAM | Infrastructure as Code | KServe | Kubeflow | Kubernetes | Lineage Tracking | MLflow | Model Drift | Model Drift Detection | Model Monitor | Model Registry | OpenTelemetry | Prometheus | Prompt versioning | Python | RAG | Sagemaker Pipelines | Secrets Manager | Seldon | Snowflake | Terraform | Vector Databases | “as-code”
Education
N/A
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