ML Engineer (General)- Remote, 3-Month Contract, Extendable

The ML Engineer (General) supports the AI / ML components of the project beyond just language processing. This role focuses on developing and optimizing various models and algorithms that drive the compliance logic and data processing. They design the non-LLM machine learning or heuristic methods needed to interpret rules and analyze BIM data – for

example, classification models, parameter extraction routines, and optimization of the overall ML pipeline. In essence, this engineer ensures that the compliance checking logic is mathematically sound, efficient, and well-integrated, providing a backbone that enhances the LLM’s outputs (e.g. through preliminary classification or data conditioning) mdpi.com .

Key Responsibilities

• Compliance Logic Development : Work with domain experts to formalize how compliance rules will be checked. This may involve translating the LLM-extracted rules into code or algorithms (for instance, encoding acceptability criteria like thresholds or boolean conditions). They might develop rule-checking algorithms or simple machine-learning classifiers to decide if a given model scenario passes or fails a rule.
• Preprocessing s Classification Models : Develop supporting ML models to preprocess regulation text or BIM data. For example, create a text classification model to categorize regulatory clauses by topic or type (fire safety, structural, accessibility, etc.) mdpi.com , which can route text to appropriate handling or

improve the accuracy of the LLM’s extraction by providing context. These models could include traditional NLP classifiers or even computer vision models if checking drawings / diagrams (if any).

= 90 cm as acceptable) and whether any exceptions need to be coded.

Required Skills and Qualifications

Preferred Experience

experience would help in seamlessly supporting the LLM engineer’s efforts.

(doesn’t have to be BIM) – such as developing validation rules for data quality, business logic engines, or even game rule engines. Understanding how to structure and evaluate complex rule sets will be beneficial.