MLE, ML Platform
Tasks
- Apply knowledge distillation to compress and optimize language models
- Build evaluation pipelines for entity linking retrieval and semantic consistency
- Collaborate with data and infrastructure engineers to productionize research
- Develop new extraction tagging resolution algorithms
- Implement scalable ML training and inference components
- Improve retrieval ranking reasoning performance with feedback loops
- Prototype models for extracting structured knowledge from text
- Read and implement research in LLM alignment distillation and symbolic grounding
- Use reinforcement learning and feedback loops to improve model behavior
Perks/Benefits
Skills/Tech-stack
BERT | C++ | Curriculum learning | Entity Linking | Evaluation metrics | Human Feedback | Information Retrieval | Knowledge Distillation | Language Models | Language Processing | Large Language Models | Learning from Human Feedback | Loss Functions | Machine Learning | Natural Language | Natural Language Processing | PyTorch | Python | Ranking | Reinforcement Learning | Reinforcement Learning from Human Feedback | Semantic Consistency | TensorFlow | Training pipelines | Transformers
Education
N/A
Regions
Countries
States
Cities
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