Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
JobTailor Logo

See all jobs on JobTailor

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
C the Signs

Senior Machine Learning Engineer

C the Signs

Machine Learning Engineer responsible for end-to-end development of AI models in healthcare. Collaborating on data processing, model training, and integration while ensuring compliance and security.

Posted 4/28/2026full-timeRemote • Massachusetts, New Hampshire, New Jersey, New York, Rhode Island • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies
AWSCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchRayScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact
  • Position SummaryThe 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

What you’ll need
  • - 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

Comp & perks
  • **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.

ATS Keywords

✓ Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learninglarge language modelsdata preprocessingmodel trainingfine-tuningPythonTensorFlowPyTorchScikit-learncloud platforms
Soft Skills
problem-solvinganalytical skillscommunicationcollaborationindependenceteamwork