AI Research Engineer (Applied AI)
Tasks
- Build training and inference pipelines
- Contribute to model monitoring and continuous improvement
- Design applied AI solutions
- Develop dataset construction and monitoring tooling
- Document research and production characteristics
- Implement experimentation workflows
- Mentor engineers on applied ML
- Optimize models for accuracy latency throughput cost
- Perform safety fairness reliability evaluations
- Translate business problems into ML formulations
Perks/Benefits
- N/A
Skills/Tech-stack
Ablation Studies | Accelerator hardware | Computer Vision | Data Quality | Data quality monitoring | Dataset labeling | Deep learning | Distributed Training | Experimentation | Fairness evaluation | Fine Tuning | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Observability | Natural Language | Natural Language Processing | Production Deployment | PyTorch | Python | Quality monitoring | Recommendation Systems | Reliability evaluation | Retrieval-Augmented Generation | Safety evaluation | Statistical Evaluation
Education
Roles
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