Research Engineer
Tasks
- Build RL environments execution and verification harnesses
- Build memory and context machinery
- Build offline evaluation harness
- Build post training stack
- Build representation layer ontologies and knowledge graphs
- Design data generation and curation pipelines
- Establish reproducibility and experiment tracking standards
- Implement quantization and model serving configuration
- Optimize training and inference throughput
- Run experiments end to end
Perks/Benefits
- N/A
Skills/Tech-stack
Context modeling | Curriculum learning | Data Curation | Distributed Training | Experiment tracking | GPU Computing | Inference | JAX | Knowledge graphs | Long Context | Long Context Modeling | Model Serving | Ontologies | PyTorch | Python | Quantization | RLAIF | RLHF | Regression testing | Reinforcement Learning | Reproducibility | Synthetic data
Education
N/A
Roles
Regions
Countries
States
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