Mandatory Experience

- Robust exposure to LLM frameworks (DSPy, LangChain, Hugging Face, or equivalent).
- Comfortable working with Databricks / MLflow or other cloud ML environments.
- Familiarity with Python and libraries like pandas, scikit-learn, or PyTorch.
- Background in Computer Science, Data Science, or AI/ML (recent grad/PHD with relevant work experience may be considered).
- Detail-oriented with strong organizational skills for tracking experiments.

Skills Experience and Skill Set Requirements Key Responsibilities Run and Monitor Inferences

- Execute batch inference jobs on Databricks and other environments.
- Troubleshoot inference issues, log results, and escalate model anomalies.

Pipeline & Evaluation Support




- Assist with running DSPy pipelines and loading custom models/configs.
- Support evaluation runs using internal metrics
- Track and summarize performance metrics for inference experiments.

Data Handling & Experimentation
- Help prepare and clean legal text datasets for inference and evaluation.
- Annotate outputs to support error analysis and benchmarking.

Maintain reproducible scripts/notebooks for inference runs. Evaluation Criteria: Technical Skills - 50% LLM frameworks - 25% Databricks/MLflow - 25%

📌 CLDRData Science/AI /ML Developer - Toronto
🏢 Cloud Resourcing
📍 Toronto