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Senior Machine Learning Engineer

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model training, and fine-t...

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C the Signs Rhode Island, United States Source published Apr 28, 2026 Verified 1 hour ago
✓ 92% verification score · Source: C The Signs Careers · Always confirm final requirements on the original source.
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EmploymentFull Time
Work modeRemote / location-flexible
CountryUnited States
Job functionEngineering
IndustryHospital & Health Care

Overview

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model training, and fine-tuning using large-scale healthcare datasets. This role requires a strong understanding of Large language models, machine learning principles, data engineering, and experience working with sensitive healthcare data. Key Responsibilities Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets for machine learning model development. This includes handling missing values, outlier detection, feature engineering, and data normalization. Identify, collect, and curate relevant, industry-specific datasets for model retraining. Format data appropriately for the chosen LLM and training pipeline Model Training & Fine-Tuning: Design, train, and f

Full job description

Full Job Description

Position Summary

The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model training, and fine-tuning using large-scale healthcare datasets. This role requires a strong understanding of Large language models, machine learning principles, data engineering, and experience working with sensitive healthcare data.

Key Responsibilities

  • Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets for machine learning model development. This includes handling missing values, outlier detection, feature engineering, and data normalization. Identify, collect, and curate relevant, industry-specific datasets for model retraining. Format data appropriately for the chosen LLM and training pipeline
  • Model Training & Fine-Tuning: Design, train, and fine-tune various LLMs on extensive healthcare data to solve specific clinical or operational problems. Set up and manage the training environment, including GPU instances and required software. Train and fine-tune pre-trained LLMs on the custom dataset to achieve specific goals. Experiment with and fine-tune hyperparameters such as learning rate, batch size, and training epochs to optimize model performance. Integration of structured + unstructured data (multi-modal/multi-input models)
  • Model Evaluation & Optimization: Evaluate model performance using appropriate metrics, identify areas for improvement, and implement optimization strategies.
  • Pipeline Development: Develop and maintain robust and scalable data and ML pipelines for model training, inference, and deployment.
  • Collaboration: Work closely with data scientists, clinicians, and software engineers to understand requirements, integrate models into production systems, and ensure data privacy and security compliance.
  • Research & Development: Stay up-to-date with the latest advancements in machine learning and healthcare AI, and explore new technologies and methodologies to enhance our solutions.
  • Documentation: Maintain clear and comprehensive documentation of models, data pipelines, and experimental results.

Requirements

  • Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.

  • Experience:

  • 5+ years of experience in Machine Learning Engineering or a similar role.

  • Proven experience with large-scale data preprocessing, LLM/model training, and fine-tuning.

  • Experience with distributed training (PyTorch Distributed, DeepSpeed, Ray, Hugging Face Accelerate).

  • Experience with GPU/TPU optimization, memory management for large language models.

  • Experience working with healthcare data is highly desirable.

  • Technical Skills:

  • Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).

  • Strong understanding of various machine learning algorithms,Large Language Models, and deep learning architectures.

  • Experience with cloud platforms (e.g., GCP, AWS) and distributed computing frameworks (e.g., Spark) is a plus.

  • Familiarity with MLOps practices and tools.

  • Soft Skills:

  • Excellent problem-solving and analytical skills.

  • Strong communication and collaboration abilities.

  • Ability to work independently and as part of a team in a fast-paced environment.

  • Work Authorization:

  • Must be a US Citizen, Green Card holder, or currently in the US have valid H1B visa

Benefits

Why Join Us?

Joining C the Signs is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact.

Benefits:

  • Competitive salary and benefits package.
  • Flexible working arrangements (remote or hybrid options available).
  • The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
  • Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
  • Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

Qualifications And Requirements

Mid-Senior level

Requirements & qualifications

Mid-Senior level

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