Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field
• 5+ years of experience in Machine Learning Engineering or similar roles
• Proven expertise in large-scale data preprocessing, model training, and fine-tuning of language models
• Experience with distributed training frameworks such as PyTorch Distributed, DeepSpeed, Ray, or Hugging Face Accelerate
• Hands-on experience with GPU/TPU optimization and memory management for large models
• Experience working with healthcare data is highly desirable
• Proficiency in Python and ML libraries including TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy
• Strong understanding of deep learning architectures and various machine learning algorithms
• Familiarity with cloud platforms like GCP, AWS, and distributed computing frameworks such as Spark is a plus
• Knowledge of MLOps practices and tools
• Excellent problem-solving, analytical, and communication skills
• Ability to work independently and collaboratively in a fast-paced environment
• Work authorization: Must be a US Citizen, Green Card holder, or in the US with a valid H1B visa

Responsibilities

• Clean, transform, and prepare large, complex healthcare datasets for machine learning model development, including handling missing data, outliers, feature engineering, and normalization
• Identify, collect, and curate relevant healthcare datasets for model retraining and validation
• Design, train, and fine-tune large language models on healthcare data to address specific clinical and operational challenges
• Manage training environments utilizing GPU instances and relevant software tools to optimize model performance
• Experiment with hyperparameters such as learning rate, batch size, and training epochs to enhance model accuracy and efficiency
• Integrate structured and unstructured data to develop multi-modal or multi-input models
• Evaluate model performance using appropriate metrics, identify areas for improvement, and implement optimization strategies
• Develop, maintain, and optimize scalable data and machine learning pipelines for training, inference, and deployment
• Collaborate closely with data scientists, clinicians, and software engineers to understand requirements and ensure seamless integration of AI solutions into production systems
• Ensure compliance with data privacy, security standards, and healthcare regulations throughout development and deployment
• Stay updated with the latest advancements in AI, healthcare technology, and related research to incorporate innovative solutions
• Maintain comprehensive documentation of models, data pipelines, and experimental results for transparency and reproducibility

Benefits

• Competitive salary and comprehensive benefits package
• Flexible working arrangements including remote and hybrid options
• Opportunity to work on impactful AI healthcare solutions that directly improve patient outcomes
• Access to cutting-edge tools, technology, and continuous learning resources in AI and healthcare
• Supportive and inclusive work environment fostering professional growth and innovation
• Participation in a mission-driven organization dedicated to health equity and technological advancement

Equal Opportunity

C the Signs is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other protected status.