Senior Applied AI Researcher (Dublin, CA)
Tasks
- Build agent orchestrated data and training pipelines
- Build hybrid retrieval architectures
- Build knowledge graph pipelines
- Continuously evaluate model systems
- Contribute to internal knowledge infrastructure
- Deploy prototypes to production systems
- Design agent driven experiment campaigns
- Design scalable solutions
- Document research findings
- Identify workflow bottlenecks
- Implement automated integration testing
- Implement structured reasoning systems
- Lead multi stage model training pipelines
- Mentor AI researchers
- Optimize models with reinforcement learning
- Own end to end research projects
- Train multimodal systems
Perks/Benefits
- N/A
Skills/Tech-stack
Automated testing | Continuous Evaluation | Data parallelism | Deep learning | DeepSpeed | Distributed Training | FSDP | Gradient Norms | Human Feedback | Hybrid retrieval | Hyperparameter Tuning | Knowledge graphs | Kubernetes | LLM | Learning from Human Feedback | Loss Curves | Machine Learning | Megatron-LM | Model Parallelism | Multimodal Learning | Python | Reinforcement Learning | Reinforcement Learning DPO | Reinforcement Learning from Human Feedback | Retrieval-Augmented Generation | Reward Modeling | Structured reasoning
Education
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