Machine Learning Engineer, John Snow Labs

Large Language Models

Salary not provided

USD 30 - USD 60 - hourly

PyTorch

Senior and Expert level

Remote from Canada, Europe, UK, US

AI & Natural Language Processing for healthcare

Be an early applicant

AI & Natural Language Processing for healthcare

21-100 employees

HealthcareB2BArtificial IntelligenceEnterpriseSaaSMedTech

Be an early applicant

Salary not provided

USD 30 - USD 60 - hourly

PyTorch

Senior and Expert level

Remote from Canada, Europe, UK, US

21-100 employees

HealthcareB2BArtificial IntelligenceEnterpriseSaaSMedTech

Company mission

We help our customers put AI to good use faster.

Job

Company

Role

Who you are

The ideal candidate will have a robust background in machine learning, natural language processing (NLP), and Large Language Models (LLMs)
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

What the job involves

We are seeking a highly skilled and experienced Machine Learning Engineer to join our team
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
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

Our take

AI has become an increasingly valuable tool for healthcare companies, but deploying AI can be time-consuming, complex and expensive. John Snow Labs solves this problem using industry-leading software, data and models.

The company has built a range of products and solutions, including its Spark NLP, which provides scalable, trainable versions of natural language processing research. It has seen impressive growth in the last few years, boasting the likes of Roche and GE Healthcare as customers, and acquiring biomed AI company WiseCube in 2025.

Having built the largest and most popular NLP library in the enterprise, John Snow Labs will need to continue to develop and build out its solutions if it is to maintain this success.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

3% employee growth in 12 months

Glassdoor (4)

Company

Company benefits

Fully virtual company

Leadership

David Talby

(CEO)

Previously worked as Senior Manager of Software Development at Amazon, and Principal Group Manager at Microsoft.

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