AI Research Engineer (Applied AI)
Tasks
- Build training and inference pipelines
- Collaborate with ML Platform engineers
- Design applied AI solutions
- Develop dataset construction and monitoring tooling
- Document research and operational characteristics
- Implement experimentation workflows
- Implement safety fairness reliability evaluations
- Mentor engineers on applied ML methodology
- Optimize models for accuracy latency throughput cost
- Prototype and evaluate ML models
- Translate business problems into ML formulations
Perks/Benefits
- N/A
Skills/Tech-stack
Ablation Studies | Accelerator hardware | Data Quality | Data Validation | Data labeling | Data quality monitoring | Deep learning | Distributed Training | Evaluation | Experimentation | Fine Tuning | Inference pipeline | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Alignment | Multimodal | Natural Language | Natural Language Processing | Observability | PyTorch | Python | Quality monitoring | Recommendation Systems | Responsible AI | Retrieval | Retrieval-Augmented Generation | Statistical Evaluation | Structured data | Training Pipeline | Vision
Education
Roles
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