AI Research Engineer (Applied AI)
Tasks
- Build training and inference pipelines
- Collaborate with product and domain experts
- Contribute to AI roadmap with research insights
- Design applied AI solutions
- Develop dataset construction and monitoring tooling
- Develop experimentation workflows
- Document research findings and operational characteristics
- Implement safety fairness and 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
Skills/Tech-stack
Ablation Studies | Accelerator hardware | Agentic Systems | Computer Vision | Data Quality | Data labeling | Data quality monitoring | Deep learning | Distributed Training | Experimentation | JAX | Language Models | Language Processing | Large Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Model Alignment | Model Evaluation | Multimodal Models | Natural Language | Natural Language Processing | Observability | PyTorch | Python | Quality monitoring | Recommendation Systems | Responsible AI | Retrieval-Augmented Generation | Statistical Evaluation | Structured data
Education
Roles
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