ML/AI Research Engineer
Tasks
- Apply ML frameworks to solve business problems
- Build reusable research tools and pipelines
- Build scalable AI systems
- Design transformer foundation models
- Develop ML apps and algorithms
- Develop ML domain expertise
- Enhance data pipelines for machine learning
- Evaluate model outputs in downstream applications
- Implement reproducible research
- Measure business impact
- Monitor evaluate and optimize learning processes
- Process structured and unstructured datasets
- Run machine learning experiments
- Track state of the art research
- Train and retrain models to prevent drift
- Train and scale deep learning models
Perks/Benefits
Skills/Tech-stack
Automated testing | CI/CD | Data Pipelines | Deep learning | Distributed Processing | Language Models | Large Language Models | Machine Learning | PySpark | PyTorch | Python | Reproducibility | Statistical Analysis | Transformer | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Engineering | Master of Science | PhD
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