[2026] Senior Machine Learning Engineer (Systems), Embodied AI/NPCs, ML Platform - PhD Early Career
Tasks
- Analyze performance and stability
- Architect distributed inference systems
- Build AI platform serving layer
- Deploy scalable high availability architectures
- Develop data pipelines
- Implement training and inference control planes
- Maintain model registry
- Manage model inference deployment
- Optimize inference engine low latency
- Optimize models with continuous batching
- Optimize models with quantization
- Optimize models with speculative decoding
- Optimize real-time inference
- Orchestrate ML pipelines
- Train deep learning models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | Cloud platform | Continuous batching | Deep learning | Distributed Systems | GPU | Google Cloud | Google Cloud Platform | Kubernetes | Language Models | Language Processing | Large Language Models | Machine Learning | Model Inference | Model Training | Natural Language | Natural Language Processing | Quantization | Speculative decoding
Education
Regions
Countries
States
Cities
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