AI Research Engineer (Applied AI)
Tasks
- Build production training and inference pipelines
- Collaborate with ML platform engineers on compute and storage
- Design prototype and evaluate applied AI solutions
- Develop tooling for dataset construction labeling validation and monitoring
- Document research findings and operational characteristics
- Implement experimentation workflows with baselines ablations and evaluation
- Implement safety fairness and reliability evaluations
- Mentor engineers on applied ML methodology and responsible deployment
- Optimize models for accuracy latency throughput and cost
- Translate business problems into ML formulations
Perks/Benefits
Skills/Tech-stack
Accelerator hardware | Computer Vision | Data Quality | Data quality monitoring | Deep learning | Distributed Training | Fine Tuning | Inference Pipelines | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Evaluation | Model Observability | Natural Language | Natural Language Processing | PyTorch | Python | Quality monitoring | Recommendation Systems | Retrieval-Augmented Generation | Statistical Evaluation | Training pipelines
Education
Roles
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