AI Research Engineer
Tasks
- Build training and inference pipelines
- Conduct safety fairness and reliability evaluations
- Design applied AI solutions
- Develop dataset construction labeling and validation tooling
- Document research findings and operational characteristics
- Implement data quality monitoring
- Mentor engineers on applied ML methodology
- Optimize models for accuracy latency throughput and cost
- Prototype and evaluate ML models
- Translate business problems into ML formulations
Perks/Benefits
Skills/Tech-stack
Accelerator hardware | Data Quality | Data quality monitoring | Deep learning | Distributed Training | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Evaluation | Natural Language | Natural Language Processing | Observability | PyTorch | Python | Quality monitoring | Recommendation Systems | Retrieval-Augmented Generation | Statistical Evaluation | Vision
Education
Roles
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