hirly

GE HealthCare

Large Language Model R&D Engineer

Shanghai · BeiJing

See how you match this job — and similar ones. Free.

Upload your resume and hirly scores it against this role at GE HealthCare first, then against similar open jobs, and shows where you fit and why.

PDF or DOCX, up to 12MB. No sign-up to see your matches.

Get past the screening software and onto a recruiter's desk

hirly rewrites your resume for this job — matching the keywords and skills in the posting, moving your most relevant experience to the top, and writing a cover letter to fit. About 30 seconds.

  • Keywords matched to this posting
  • Fit score before you apply
  • Cover letter included
Tailor my resume for this job →

Apply from your AI assistant

Connect hirly to Claude and ask it to apply to this job. hirly tailors your resume, fills the employer’s form and asks before sending. ChatGPT: manual setup today.

Some employer sites stop an application at a CAPTCHA or sign-in and hand it back with a link. Applying needs a paid plan. Works with any assistant that supports MCP.

hirly's read of this role

Seniority
Mid level
Country
CN
Work mode
On-site / unstated
First seen by hirly
15 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Job Description Summary

  • Develop and optimize LLM, VLM, embedding, and audio multimodal models based on
  • open-source foundation models. Build GUI-recognition and automated-control agents for medical
  • post-processing software and medical devices, meeting product design, performance, and
  • compliance-validation requirements. This role does not involve large-scale foundation-model
  • pretraining.

GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world. tex

Job Description

Multimodal Fine-Tuning & Agent Development

Fine-tune LLM, VLM, embedding, and audio models using PEFT methods including LoRA/QLoRA, SFT, and DPO.

Deliver GUI recognition, UI-element localization, instruction understanding, task planning, and tool-calling capabilities for device and software automation.

Data, Evaluation & Traceability

Build multimodal datasets from software screenshots, workflows, device commands, and audio interactions; perform collection, cleaning, annotation, and augmentation.

Establish automated evaluation for recognition accuracy, instruction-following success, hallucination rate, and robustness; maintain versioning and experiment records for R&D traceability.

Model Optimization & Deployment

Apply distillation, pruning, and INT4/INT8 quantization (PTQ/QAT) to reduce model size, memory, and compute cost while preserving accuracy.

Optimize inference through KV cache, operator fusion, and memory reuse; convert and deploy models locally using TensorRT and ONNX Runtime to meet latency and throughput targets.

Integration, Validation & Research

Integrate VLM interface recognition, LLM planning, embedding retrieval, and ASR understanding into an automated agent loop with engineering teams.

Support model verification, performance validation, technical documentation, risk analysis, boundary-case analysis, and evaluation of emerging VLM, Agent, GUI, and lightweight-model technologies.

Qualifications

Education

Master's degree or above in Computer Science, Artificial Intelligence, Pattern Recognition, Biomedical Engineering, or a related field.

Fundamental Knowledge

Strong understanding of Transformer architectures, LLMs, VLMs, and PyTorch.

Hands-on end-to-end experience with SFT and parameter-efficient fine-tuning such as LoRA/QLoRA.

Required Technical Skills

Experience with VLMs (for example, LLaVA), GUI/screenshot visual understanding, and automated-control tasks.

Knowledge of embedding models, RAG, and ASR model tuning.

Knowledge of distillation, quantization, pruning, TensorRT, and ONNX Runtime.

Proficiency in Python and Linux; ability to independently build datasets, train and evaluate models, and complete model conversion and deployment.

Preferred Qualifications

Experience in medical devices, medical-imaging post-processing software, medical-device AI, or medical-device software quality systems.

Practical experience with agent development, tool calling, and orchestration frameworks such as LangChain or LangGraph.

Experience optimizing models for embedded or compute-constrained local devices; familiarity with C++, inference SDKs, or vector databases.

Professional Competencies

Strong focus on experiment traceability, model boundaries, and risk management.

Sound engineering judgment to balance accuracy, latency, and hardware cost.

Effective cross-functional collaboration with device software, Product, and Quality teams

Inclusion and Diversity

GE HealthCare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support.

Original posting on GE HealthCare's site ↗

Listed on hirly, a job board. hirly is not the employer: GE HealthCare is hiring for this role.

Browse similar roles

Want this one?

Upload your resume and hirly rewrites it for this job and writes the cover letter — in about thirty seconds, before you sign up.

Tailor my resume for this job