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Senior Machine Learning Engineer (Remote - US) at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer in the United States.. As a Senior Machine Learning Engineer, you will design and deploy advanced AI solutions that directly accelerate clinical research and improve patient outcomes. You will build scalable ML models, LLM-powered agents, and robust data pipelines, working in a highly collaborative, remote-friendly environment. This role offers the opportunity to turn cutting-edge AI research into production-ready solutions, impacting real-world workflows across research sites and stakeholders. You will collaborate with product managers, engineers, data scientists, and domain experts to integrate ML capabilities seamlessly into existing platforms. Your contributions will improve patient recruitment, enrollment forecasting, and study feasibility, while ensuring reliability, scalability, and compliance. Innovation, analytical rigor, and mission-driven focus are at the heart of this role.. . Accountabilities. In this role, you will:. . Design, build, and deploy ML-driven products that accelerate clinical trials and enhance patient outcomes.. . Develop advanced models and LLM-powered agents for critical applications such as patient recruitment, study feasibility, and enrollment forecasting.. . Implement modern MLOps best practices, building scalable data pipelines and deploying models in cloud environments with monitoring and automation.. . Collaborate with cross-functional teams, integrating ML solutions into the platform to improve clinical research workflows for end-users.. . Continuously explore new ML/AI methods, evaluate prototypes, and transition successful experiments into production features.. . Maintain clear documentation and ensure models adhere to reliability, security, and performance standards.. . . Candidates should have:. . 5+ years of hands-on ML engineering experience, deploying production-ready solutions at scale.. . Strong programming and data skills in Python, with experience in ML frameworks (TensorFlow/PyTorch, scikit-learn) and data processing libraries (pandas, SQL).. . Experience with cloud infrastructure (AWS or similar) and containerization tools (Docker); familiarity with MLOps best practices including CI/CD, monitoring, and automated testing.. . Deep understanding of ML fundamentals: model selection, feature engineering, training, evaluation, and statistical modeling.. . Familiarity with NLP and large language models (LLMs).. . Strong analytical problem-solving skills with the ability to design pragmatic, performant, and maintainable ML solutions.. . Mission-driven mindset, with empathy for patients, researchers, and clinicians; commitment to building unbiased, responsible AI systems.. . Experience with functional programming (e.g., Clojure) is a plus but not required. Company Location: United States.