Manager, ML Engineering
Tasks
- Align platform patterns APIs and service contracts
- Champion AI assisted engineering productivity
- Contribute to AI service roadmap and delivery
- Coordinate with product management and TPM
- Deploy ML models to production
- Establish model evaluation and monitoring
- Handle model promotion and rollback
- Implement automated quality gates
- Integrate and validate model handoff
- Lead and mentor ML engineers
- Maintain model deployment pipeline
- Maintain operational SLOs reliability and incident response
- Manage distributed team across geographies
- Own end to end delivery to production
- Partner with applied machine learning team
- Plan scope and manage release management
- Run shadow canary and rollout stages
- Track quality performance drift and SLO compliance
Perks/Benefits
Skills/Tech-stack
AWS Bedrock | AWS SageMaker | Agent Orchestration | Agentic Workflows | Amazon EKS | Audio analytics | Blue-Green Deployment | Blue/green | Canary Deployment | Drift Detection | Experiment tracking | Incident Management | Inference Server | Kafka | Kotlin | Kubernetes | Language Processing | MLOps | Model Registry | Model Rollback | Multi-Agent | Multi-agent orchestration | NEMO | Natural Language | Natural Language Processing | Observability | On-Call | Parakeet | Python | Quality gates | RAG | SLOs | Shadow Deployment | Transformer Models | Triton Inference | Triton Inference Server | XLM-R
Education
N/A
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