Machine Learning Engineer, Assessment Intelligence

About This Role

Responsibilities

• Build evaluation pipelines for LLM scoring, evidence extraction, rubric alignment, and voice assessment components.
• Design tests for prompt variation, input noise, prompt injection, multilingual quality, and model drift.
• Develop monitoring around scoring stability, confidence, and anomalous candidate behavior.
• Collaborate with science on CTT, IRT, CFA, DIF, fairness, and human-AI benchmarking workflows.
• Prototype predictive models connecting assessment results to job fit, retention, and performance evidence where data is available.
• Productionize AI components with clear interfaces, versioning, and observability.

Requirements

• 3+ years in ML engineering, applied AI, data science, or adjacent production AI work.
• Strong Python skills and comfort with statistical analysis, model evaluation, and data pipelines.
• Hands-on experience with LLMs, NLP, speech, or multimodal evaluation.
• Understanding of fairness, bias testing, model monitoring, and responsible AI practices.
• Ability to translate technical findings into product decisions and customer-facing evidence.
• Strong software engineering habits and comfort shipping production code.