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About the Role
Lumexa Imaging is hiring an early-career AI Engineer to build, adapt, and deploy vision language models (VLMs) and imaging foundation models for clinical radiology. You will work hands-on using agentic coding tools to transition ideas from radiologists into validated, deployed models. This is a build-focused role centered on model development and deployment, with initial priorities including building clinical LLM pipelines.
Responsibilities
- Fine-tune and adapt open VLMs and imaging foundation models for report drafting, impression generation, finding detection, and prior comparison.
- Apply parameter-efficient methods (LoRA, QLoRA) and full fine-tuning under senior guidance.
- Work with vision encoders, contrastive image-text models, and self-supervised approaches.
- Build and maintain embedding pipelines for retrieval, cohort discovery, case similarity search, and drift detection.
- Curate and version datasets from internal PACS and reporting systems, including DICOM header, burned-in pixel, and paired-report de-identification.
- Use Claude Code and OpenAI Codex daily to build, test, and maintain code.
- Maintain project context (CLAUDE.md, AGENTS.md), and help build and run MCP servers for internal system access.
- Deploy models via containerized inference and GPU serving (vLLM, Triton).
- Support CI/CD pipelines, and monitor production models for drift and performance.
- Build automated evaluation harnesses for clinical accuracy, negation, laterality, and hallucination scoring against radiologist ground truth.
- Build agentic and LLM driven tools for operational workflows, such as converting unstructured requests into RIS scheduling actions and supporting intelligent operations dashboards.
Requirements
- Hands-on experience fine-tuning transformer models in PyTorch (vision, multimodal, or language) using Hugging Face, MONAI, or similar (via internships, research, open-source work, or projects).
- Working knowledge of embeddings and vector search.
- Experience with open VLMs such as Qwen-VL or LLaVA.
- Daily use of agentic coding tools (Claude Code, OpenAI Codex).
- Familiarity with Docker and GPU-based model serving.
- Comfort working with real-world data and a reproducible approach to experiments.
Skills
- PyTorch
- Hugging Face
- MONAI
- Embeddings
- Vector search
- Qwen-VL
- LLaVA
- Claude Code
- OpenAI Codex
- Docker
- GPU-based model serving
- Vision encoders
- Contrastive models (CLIP, SigLIP, JEPA)
- Medical VLMs
- Imaging foundation models
- Self-supervised methods (DINOv2, MAE)
- MCP servers
- DICOM
- HL7
- FHIR
- HIPAA/PHI handling
- MLOps tooling (MLflow, Weights & Biases, model registries)
- FDA considerations for clinical AI (510(k), PCCP)
Location
- Remote
Work Type
- Remote
- Full-time
Experience Level
- Early-career
- 0 to 3 years
Education Level
- Degree in Computer Science, Biomedical Engineering, or a related field (or equivalent practical experience)
About the Company
- Lumexa Imaging is one of the country's largest providers of outpatient medical imaging.
- With over 5,000 team members and more than 185 outpatient imaging centers across 13 states, our team conducts more than 4 million outpatient studies annually.
- We are the partner of choice for health systems and radiologists, delivering best-in-class clinical excellence, operations, and state-of-the-art technology across our platform.
Equal Opportunity
- Lumexa Imaging is an equal opportunity employer.