Research Engineer - Applied AI/ML
Tasks
- Apply state of the art machine learning techniques
- Apply transformer architectures and large language models
- Architect and own ML modules
- Build ML and DL solutions
- Develop and deploy machine learning services
- Develop and design model features
- Evolve machine learning products
- Implement MLOps pipelines
- Implement reinforcement learning solutions
- Optimize model performance with pruning and quantization
- Process large scale datasets in distributed systems
- Productionize ML models
Perks/Benefits
- N/A
Skills/Tech-stack
Concurrency systems | Deep learning | Distributed Computing | High concurrency | High-concurrency systems | Language Models | Large Language Models | Linear Algebra | MLOps | Machine Learning | Neural Networks | Optimization | Pruning | Python | Quantization | Reinforcement Learning | Transformers
Education
Roles
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