Senior Machine Learning Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 17h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 140d ago
The date the source published, not the day we noticed it (2026-04-28). Last seen at its source 2h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $160.1k–208.7k/yr
Middle 50% of 743 listings that do state pay — Engineering · Senior · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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workable employer's own board first seen 11d ago · last seen 2h ago
The listing
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.