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.

Qualifications
Background in Computer Science, Data Science, or AI/ML (student or recent grad is valuable).
Familiarity with Python and libraries like pandas, scikit-learn,



or PyTorch.
Exposure to LLM frameworks (DSPy, LangChain, Hugging Face, or equivalent).
Comfortable working with Databricks / MLflow or other cloud ML environments.
Detail-oriented with solid organizational skills for tracking experiments.

Evaluation:
Technical Skills - 50%
LLM frameworks - 25%
Databricks/MLflow - 25%

Must have:
must have experience Azure data tools - azure, databricks, MLflow, python
Exposure to LLM frameworks (DSPy, LangChain, Hugging Face, or equivalent).
Familiarity with Python and libraries like pandas, scikit-learn, or PyTorch.,

📌 Ai/ml Engineer Toronto (Canada)
🏢 BuzzClan
📍 Canada