Role overview
**LLM Engineer – Geotechnical Data Digitization**
*Location: Remote*
*Engagement Type: Contract (Full-Time, 40 hours/week)*
*Duration: an initial 8-10 weeks, with strong likelihood for extension into future phases (Up to 1 year in length)*
**Role Overview:**
We are seeking a highly skilled LLM Engineer to assist in the development of a multi-modal Large Language Model (LLM) pipeline for digitizing geotechnical bore log data. This role is critical to transforming unstructured PDF documents into structured, machine-readable JSON outputs that support downstream analytics, GIS integration, and AI-powered search.
You will work closely with a Project Manager and technical stakeholders at our customer to build, fine-tune, and evaluate a custom LLM solution capable of interpreting complex geotechnical documents across multiple vendors.
**Key Responsibilities:**
Phase 1 –
Pilot Development
* Fine-tune a multi-modal LLM (e.g., Pixtral-12B, PaliGemma, Gemma 3) using annotated bore log PDFs and JSON samples.
* Build preprocessing pipelines for: Page segmentation, Figure isolation, Normalization of units and soil classification.
* Develop and implement an evaluation framework including Precision/Recall/F1, domain-specific metrics, and JSON schema conformance.
Cross-Vendor Generalization
* Test model generalization on bore logs from 3 additional vendors.
* Identify and categorize failure cases.
* Compare performance across vendors and recommend strategies for scaling.
Pipeline Packaging & Handoff
* Package preprocessing scripts, model artifacts, and evaluation dashboards into a reproducible workflow.
* Deliver structured JSON outputs and final benchmark reports.
* Provide all source code and documentation for handoff.
**Required Qualifications:**
* Proven experience fine-tuning and deploying multi-modal LLMs (e.g., Pixtral, LLaMA, Gemma, etc.)
* Ollama/llama.ccp, mongodb/non-relational dbs, and ai coding tools (cursor/windsurf/co-pilot.) experience.
* Experience using OSS models
* Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
* Experience with OCR, image preprocessing (OpenCV), and document parsing
* Familiarity with geospatial data and JSON schema design
* Ability to work with GPU environments (e.g., A100s) and cloud-based training setups
* Strong understanding of evaluation metrics and model benchmarking
* Excellent communication and documentation skills
**Preferred Qualifications (nice to have):**
* Experience with geotechnical or engineering datasets
* Familiarity with MongoDB, vector search, and embedding-based retrieval
* Exposure to MLOps practices and CI/CD for ML pipelines
* Prior work in AI document ingestion or enterprise-scale data transformation