AI Research Engineer
Tasks
- Build training and inference pipelines
- Collaborate on compute and accelerator resource utilization
- Deploy models and improve continuously
- Design applied AI solutions
- Develop dataset construction labeling and validation tooling
- Develop experimentation workflows with baselines and ablations
- Document research and deployment decisions
- Implement safety fairness and reliability evaluations
- Mentor engineers on ML methodology and evaluation
- Monitor data quality
- Optimize models for accuracy latency throughput and cost
- Prototype and evaluate ML models
- Translate business problems into ML formulations
Perks/Benefits
- N/A
Skills/Tech-stack
Ablation Studies | Accelerator hardware | Computer Vision | Data Monitoring | Data 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 Evaluation | Natural Language | Natural Language Processing | Observability | PyTorch | Python | Recommendation Systems | Reliability evaluation | Retrieval-Augmented Generation | Safety evaluation | Statistical Evaluation
Education
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