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Senior Machine Learning Engineer
C the SignsMachine 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 & technologiesAWSCloudGoogle 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 resumeApplicant 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