Applied AI Engineer
Derivative Path1 month ago
Remote, CanadaSenior
Responsibilities
- Build and ship LLM-powered features for complex financial workflows in collaboration with domain experts.
- Design production agentic workflows that can reason, act, and recover across multi-step processes.
- Own data engineering pipelines, retrieval architectures, context design, and data quality for AI systems.
- Prototype, evaluate, and productionize AI capabilities while contributing to evaluations, tooling, MLOps practices, and reusable technical patterns.
- Work as a hands-on engineer across experimentation and production and potentially contribute to NLP, model fine-tuning, synthetic data, or reinforcement learning.
Requirements
- Experience building with LLMs through prompt engineering, retrieval-augmented generation, fine-tuning, agents, or inference pipelines.
- Experience designing and building data pipelines that support real workflows.
- ML or data science experience, particularly in complex or data-constrained environments.
- Working knowledge of Python and common AI/ML frameworks such as PyTorch, Hugging Face, or LangChain.
- MLOps or production AI experience taking models from notebooks into production.
- Experience with at least one of Azure, AWS, or GCP.
- Reinforcement learning or financial derivatives experience is preferred but not required.
Benefits
- Fully remote work arrangement in Canada.
- Competitive base salary, discretionary bonus, and equity compensation.
- 23 days of paid time off.
- RRSP contribution at 3%.
- Competitive health benefits, including health, dental, and vision coverage.
Categories
AI ApplicationsData Engineering