Machine Learning Engineer – Large Language Models

Posted 2 weeks ago

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About the role

  • Machine Learning Engineer specializing in large language models for John Snow Labs. Working on AI model training and optimization for healthcare applications in a fully remote setting.

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

  • A fully virtual company, collaborating across 28 countries
  • Competitive package and compensation plan
  • Industry leader and respected brand name
  • Learning and development

Job title

Job type

Contract

Experience level

Mid levelSenior

Salary

$30 - $60 per hour

Degree requirement

Postgraduate Degree

Tech skills

C++PyTorch

Location requirements

RemoteWorldwide

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