AI Research Engineer
Tasks
- Build training and inference pipelines
- Contribute to AI roadmap planning
- Create dataset labeling and validation tooling
- Design applied AI solutions
- Develop experimentation workflows
- Document research and engineering decisions
- Mentor engineers on applied ML practices
- Monitor data quality
- Optimize models for accuracy latency throughput cost
- Orchestrate production machine learning systems
- Perform safety fairness reliability evaluations
- Prototype and evaluate machine learning models
- Translate business problems into ML formulations
Perks/Benefits
Skills/Tech-stack
Accelerators | Computer Vision | Data Quality | Data labeling | Data quality monitoring | Deep learning | Distributed Training | Experiment design | Fairness evaluation | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Observability | Multimodal | Natural Language | Natural Language Processing | PyTorch | Python | Quality monitoring | Recommender Systems | Reliability Engineering | Retrieval-Augmented Generation | Safety evaluation | Statistical Evaluation | Structured data
Education
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