Senior Machine Learning Engineer
Tasks
- Build MLOps pipelines for training fine tuning deployment monitoring
- Create production runbooks and on call support
- Design and deploy creative scoring system
- Develop model APIs embedding services and endpoints
- Implement distributed training and inference
- Lead multimodal ML model development
- Optimize training cost and inference latency
- Set up real time monitoring drift detection and alerting
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Airflow | Argo | Azure ML | CI/CD | Distributed Training | Docker | Drift Detection | Embedding pipelines | Feature Store | GCP Vertex | GCP Vertex AI | Helm | Horovod | Kubeflow | Kubernetes | LLMs | MLflow | Model Monitoring | Multimodal Learning | PyTorch | PyTorch Lightning | Python | Ray | Real Time | Real Time Retrieval | SQL | TensorFlow | Terraform | VLMs | Vector Databases | Vertex AI | Weights and Biases
Education
N/A
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