About the role
We’re hiring an Applied AI Engineer to design, fine-tune, and deploy production-grade AI models powering next-generation AI agents in financial workflows.
This role sits at the intersection of research and real-world deployment — taking models from experimentation to high-stakes production systems.
What You’ll Do
Model Development
- Fine-tune LLMs and multimodal models for domain-specific use cases
- Design post-training workflows (instruction tuning, RLHF, evaluation loops)
- Optimize training pipelines using open-source frameworks
- Run ablation studies and hyperparameter tuning
AI Agent Systems
- Build AI agents capable of executing multi-step workflows
- Integrate models into production environments
- Improve robustness, accuracy, and reliability
- Develop evaluation frameworks for edge cases
Data & Collaboration
- Work with proprietary datasets
- Build labeling and data-quality pipelines
- Partner with product and engineering teams globally
Requirements
- 1–4 years hands-on ML/AI training experience
- Strong Python + PyTorch
- Experience with Hugging Face ecosystem
- Experience deploying models to production
- Understanding of model evaluation trade-offs
Bonus: RLHF, model distillation, RAG, distributed training, GPU optimization, multi-agent systems.
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