Lead Machine Learning Engineer-MLOps
Palo Alto, CA, United States
USD 177K-215K (estimate) Senior-level Full Time
Tasks
- Build and maintain distributed training pipelines
- Collaborate cross functional teams to improve infrastructure
- Deploy large language models for efficient inference
- Develop real-time and batch inference pipelines
- Ensure production validation and system reliability
- Establish monitoring and observability pipelines
- Implement model quantization and optimization techniques
- Manage and optimize vector databases
Perks/Benefits
- Backup childcare
- Equal opportunity employment
- Financial coaching
- Health care coverage
- Mental health support
- On-site health and wellness centers
- Retirement savings plan
- Tuition reimbursement
Skills/Tech-stack
AWS | Airflow | Amazon ECS | Apache Spark | Autoscaling | Batch inference | CUDA | Caching | Database | Distributed Training | Docker | High Throughput | Kubeflow | Kubernetes | Language Models | Large Language Models | Low Latency | Machine Learning | Monitoring | Observability | Python | Quantization | Ray | Real Time | Real-time Inference | SGLang | VLLM | Vector Database
Education
Regions
Countries
States
Cities
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