SR Principal Software Engineer - LLM Engineering
Palo Alto, CA, United States
USD 175K-215K (estimate) Senior-level Full Time
Tasks
- Advise on model serving strategy and architecture
- Build reusable ML engineering platform frameworks
- Collaborate with stakeholders to prioritize AI and ML capabilities
- Define MLOps and LLMOps lifecycle management
- Deploy and optimize model inference servers
- Implement automation, CI/CD, and infrastructure-as-code
- Optimize model inference for high throughput and low latency
- Oversee AI workload operations with monitoring incident response security and compliance
- Productionize models on AWS with observability reliability and cost efficiency
- Translate technical concepts into executive strategies
Perks/Benefits
- Backup childcare
- Financial coaching
- Health care coverage
- Mental health support
- Retirement savings plan
- Tuition reimbursement
Skills/Tech-stack
AWS | Amazon Bedrock | Amazon EKS | Amazon SageMaker | Amazon SageMaker Pipelines | Autoscaling | Azure Machine Learning | CI/CD | Caching | CloudFormation | Compliance | Distributed Systems | Docker | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Governance | Hugging Face | Hugging Face Transformers | Incident Response | Inference Server | Infrastructure as Code | Java | Kubeflow | Kubernetes | MLflow | Machine Learning | Model Parallelism | Monitoring | Observability | PyTorch | Python | Quantization | SLI | SLO | Sagemaker Pipelines | Security | TensorFlow | Terraform | Throughput Optimization | Triton Inference | Triton Inference Server | VLLM | Vertex AI | “as-code”
Education
Regions
Countries
States
Cities
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