Machine Learning Engineer - Large Language Models

John Snow Labs3 months ago
Los Angeles, CA, United States
Remote
Contract
Junior Level (1-3 years)

Job Description

• Contract

Compensation: USD 30 - USD 60 per hour

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, Dev Ops and Sec Ops.

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.

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.

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.

Benefits

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

Equal Employment Opportunity

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.

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Required Skills

Prompt Engineering Fine-Tuning
Model Tuning Frameworks
Model Serving Frameworks
Natural Language Processing
PyTorch
Transformer Architectures
Model Quantization Techniques
Direct Parameter Optimization
Sparse Fine-Tuning
Large Language Models
Retriever-Augmented Generation
Proximal Policy Optimization
Machine Learning
Data Cleaning and Refinement