Machine Learning Engineer - Large Language Models
John Snow Labs1 year ago
Remote, WorldwideSenior
Responsibilities
- Adapt large language models to diverse healthcare use cases using SFT, PEFT, DPO, and PPO.
- Optimize LLMs for retrieval-augmented generation to improve decision-making and information retrieval.
- Collect, clean, and refine healthcare datasets for LLM training.
- Convert models into production-ready formats for real-world deployment.
- Collaborate with professionals in software engineering, data science, and medicine.
Requirements
- At least 5 years of hands-on professional software engineering experience building production-grade deep learning solutions.
- An academic degree in computer science, data science, or a related field.
- Expertise with the Axolotl model-tuning framework.
- Familiarity with vLLM, TGI, and llama-cpp for model serving and scalable deployment.
- Knowledge of model quantization techniques and frameworks.
- Hands-on experience with Transformer architectures and proficiency in PyTorch.
- An M.Sc. or Ph.D. degree is strongly preferred.
- Applicants must include a cover letter containing the words “John Snow Labs” and describing their academic, professional ML engineering, and recent LLM engineering experience.
Benefits
- Fully virtual work arrangement with collaboration across 28 countries.
- Competitive package and compensation plan.
- Learning and development opportunities.
- Opportunity to contribute to healthcare, life science, and open-source AI communities.
- Workplace committed to fair consideration and free from discrimination.
Tech Stack
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