AI Research Engineer
Tasks
- Build training and inference pipelines
- Contribute to knowledge sharing and prototype to production playbooks
- Design applied AI solutions
- Develop dataset construction labeling validation and monitoring tooling
- Document research findings and system characteristics
- Implement experimentation workflows with baselines and ablations
- Implement safety fairness and reliability evaluations
- Influence AI roadmap with research insights
- Mentor engineers on applied ML methodology and responsible deployment
- Optimize models for accuracy latency throughput and cost
- Prototype and evaluate machine learning systems
- Translate business problems to ML formulations
Perks/Benefits
Skills/Tech-stack
Ablation Studies | Accelerator hardware | Computer Vision | Data Quality | Data quality monitoring | Deep learning | Distributed Training | Experimentation | Fine Tuning | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Alignment | Model Deployment | Model Evaluation | Multimodal Learning | Natural Language | Natural Language Processing | Observability | Open Source | PyTorch | Python | Quality monitoring | Recommendation Systems | Responsible AI | Retrieval-Augmented Generation | Statistical Evaluation | Structured data
Education
Roles
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