Time since we first saw it
Day 155
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From 4,296 similar postings that came down. Coming down is not always a hire.
Machine Learning Engineer - Large Language Models
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Listed location: Remote, Remote, unknown
Read the full posting- Employment
Contract — employment source
Employment type in the employer’s posting: Contract
From the employer’s posting
What you’ll work on
Full postingAdapt LLMs to healthcare use cases using fine-tuning and preference-optimization methods
Optimize LLMs for retrieval-augmented generation (RAG)
Collect, clean, and refine healthcare datasets for LLM training
Convert models into formats suitable for production environments
From the employer’s posting
Adapt LLMs to diverse healthcare use-cases using techniques such as Sparse Fine-Tuning (SFT), Prompt Engineering Fine-Tuning (PEFT), Direct Parameter Optimization (DPO), and Proximal Policy Optimization (PPO).
Optimize LLMs for Retriever-Augmented Generation (RAG) to enhance decision-making and information retrieval capabilities.
Collect, clean, and refine healthcare datasets for training LLMs to ensure high-quality data provisioning.
Convert models into various formats suitable for production environments, ensuring their readiness for real-world application.
What you’ll bring
All qualificationsCore experience
- 5+ years of hands-on professional experience in software engineering, building production-grade deep learning solutions.
- Demonstrated expertise in model tuning frameworks like Axolotl.
- Familiarity with model serving frameworks, including vLLM, TGI, and llama-cpp, to support the deployment and scalability of machine learning models.
- Knowledge of model quantization techniques and frameworks to optimize AI models for performance in resource-constrained environments.
- Hands-on experience with Transformer architectures and proficiency in machine learning frameworks such as PyTorch.
Qualification wording
5+ years of hands-on professional experience in software engineering, building production-grade deep learning solutions.
Demonstrated expertise in model tuning frameworks like Axolotl.
Familiarity with model serving frameworks, including vLLM, TGI, and llama-cpp, to support the deployment and scalability of machine learning models.
Knowledge of model quantization techniques and frameworks to optimize AI models for performance in resource-constrained environments.
Hands-on experience with Transformer architectures and proficiency in machine learning frameworks such as PyTorch.
Education & alternatives
• 5+ years of hands-on professional experience in software engineering, building production-grade deep learning solutions. • An academic degree in computer science, data science, or a related degree. M.Sc. or Ph.D. degree is strongly preferred. • Demonstrated expertise in model tuning frameworks like Axolotl.
John Snow Labs is an award-winning AI and NLP company, accelerating progress in data science by providing state-of-the-art software, data, and models. Founded in 2015, it helps healthcare and life science companies build, deploy, and operate AI products and services. John Snow Labs is the winner of the 2018 AI Solution Provider of the Year Award, the 2019 AI Platform of the Year Award, the 2019 International Data Science Foundation Technology award, and the 2020 AI Excellence Award. John Snow Labs is the developer of Spark NLP - the world’s most widely used NLP library in the enterprise - and is the world’s leading provider of state-of-the-art clinical NLP software, powering some of the world’s largest healthcare & pharma companies. John Snow Labs is a global team of specialists, of which 33% hold a Ph.D. or M.D. and 75% hold at least a Master’s degree in disciplines covering data science, medicine, software engineering, pharmacy, DevOps and SecOps.
Posting record
Report an errorOpen 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026155 days ago
- Recorded sightings
- 69
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Aug 22, 2025
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
John Snow Labs is hiring
2 open jobs
Hiring recordSee how this role fits your experience
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- PyTorch
Where the posting names them
• Knowledge of model quantization techniques and frameworks to optimize AI models for performance in resource-constrained environments. • Hands-on experience with Transformer architectures and proficiency in machine learning frameworks such as PyTorch. This role offers an opportunity to be at the forefront of technological advancement in AI and healthcare, contributing to innovations that advance the healthcare, life science, and open-source AI communities. When applying, please add a cover letter which includes the words ‘John Snow Labs’ and explains your academic, professional ML engineering, and recent LLM engineering experience.
Your next step
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Job Description
We are seeking a highly skilled and experienced Machine Learning Engineer to join our team. The ideal candidate will have a robust background in machine learning, natural language processing (NLP), and Large Language Models (LLMs). The role focuses on training, tuning, and evaluating AI models as part of a diverse team which includes professionals from software engineering, data science, and medicine.
Qualifications
Key Responsibilities:
• Adapt LLMs to diverse healthcare use-cases using techniques such as Sparse Fine-Tuning (SFT), Prompt Engineering Fine-Tuning (PEFT), Direct Parameter Optimization (DPO), and Proximal Policy Optimization (PPO).
• Optimize LLMs for Retriever-Augmented Generation (RAG) to enhance decision-making and information retrieval capabilities.
• Collect, clean, and refine healthcare datasets for training LLMs to ensure high-quality data provisioning.
• Convert models into various formats suitable for production environments, ensuring their readiness for real-world application.
Requirements:
• 5+ years of hands-on professional experience in software engineering, building production-grade deep learning solutions.
• An academic degree in computer science, data science, or a related degree. M.Sc. or Ph.D. degree is strongly preferred.
• Demonstrated expertise in model tuning frameworks like Axolotl.
• Familiarity with model serving frameworks, including vLLM, TGI, and llama-cpp, to support the deployment and scalability of machine learning models.
• Knowledge of model quantization techniques and frameworks to optimize AI models for performance in resource-constrained environments.
• Hands-on experience with Transformer architectures and proficiency in machine learning frameworks such as PyTorch.
This role offers an opportunity to be at the forefront of technological advancement in AI and healthcare, contributing to innovations that advance the healthcare, life science, and open-source AI communities. When applying, please add a cover letter which includes the words ‘John Snow Labs’ and explains your academic, professional ML engineering, and recent LLM engineering experience.
Additional Information
What John Snow Labs offers:
- A fully virtual company, collaborating across 28 countries
- Competitive package and compensation plan
- Industry leader and respected brand name
- Learning and development
We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity we will give your application fair consideration.
Company Description
John Snow Labs is an award-winning AI and NLP company, accelerating progress in data science by providing state-of-the-art software, data, and models. Founded in 2015, it helps healthcare and life science companies build, deploy, and operate AI products and services. John Snow Labs is the winner of the 2018 AI Solution Provider of the Year Award, the 2019 AI Platform of the Year Award, the 2019 International Data Science Foundation Technology award, and the 2020 AI Excellence Award.
John Snow Labs is the developer of Spark NLP - the world’s most widely used NLP library in the enterprise - and is the world’s leading provider of state-of-the-art clinical NLP software, powering some of the world’s largest healthcare & pharma companies. John Snow Labs is a global team of specialists, of which 33% hold a Ph.D. or M.D. and 75% hold at least a Master’s degree in disciplines covering data science, medicine, software engineering, pharmacy, DevOps and SecOps.
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Remote, Remote
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