Remote Medical Vision-Language AI Engineer

Lumexa Imaging; San Francisco (CA); Remote; USD 120,000 - 190,000; Full time

Job summary

Lumexa Imaging seeks an early-career AI Engineer to build, adapt, and deploy vision language models and imaging foundation models for clinical radiology. You will work hands-on using agentic coding tools to translate radiologist ideas into validated, deployed models, with a build-focused emphasis on model development and deployment.

Initial priorities include clinical LLM pipelines and tooling on infrastructure shared with VLM work, with access to large imaging and reporting data under privacy

Qualifications

• Fine-tune transformer models in PyTorch (vision/multimodal/language).
• Familiar with 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 with real-world data and reproducible experiments.

Responsibilities

• VLM development and adaptation for report drafting, impression generation, and finding detection.
• Work with vision encoders and contrastive models; build embedding pipelines for retrieval and case similarity search.
• Curate datasets from internal PACS and reporting systems with de-identification.
• Use Claude Code and OpenAI Codex to build, test, and maintain code; manage project context files.

Skills

Fine-tuning PyTorch

Embeddings & vector search

Open VLMs

Agentic coding tools

Docker

GPU serving

Education

Bachelor's degree in CS/Biomedical Engineering

Tools

Hugging Face

MONAI

DICOM tooling

Docker

Job description

Lumexa Imaging seeks an early-career AI Engineer to build, adapt, and deploy vision language models and imaging foundation models for clinical radiology. You will work hands-on using agentic coding tools to translate radiologist ideas into validated, deployed models, with a build-focused emphasis on model development and deployment.

Initial priorities include clinical LLM pipelines and tooling on infrastructure shared with VLM work, with access to large imaging and reporting data under privacy