Top Healthtech Machine Learning Engineer Jobs

Develop advanced algorithms, apply machine learning, collaborate with clients, and assess new datasets and technologies for data science projects.

Lead a team of Data Scientists and Machine Learning Engineers to design and deploy machine learning solutions, enhancing customer and agent experiences. Oversee the full data science lifecycle and mentor team members, ensuring best practices in MLOps and model validation.

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

Lead end-to-end design, implementation, deployment, and operation of production AI/ML-enabled full-stack applications. Build LLM-powered features, design scalable backend services and data models, deploy on Azure, implement CI/CD and observability, and mentor engineers while ensuring secure, compliant integration into clinical workflows.

Develop and evaluate novel AI/ML solutions for healthcare using structured and unstructured data. Build and test deep learning and classical ML models, design experiments, perform statistical analysis and visualizations, document models, collaborate with stakeholders, RUAI, and engineering to productionize solutions and MLOps pipelines, and publish/patent research.

Develop and scale machine learning systems to enable AI coaching, collaborate across teams for member insights, and contribute to architectural decisions.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

Lead design, development, and deployment of enterprise AI agents and multi-agent systems. Architect scalable, secure AI/data systems, integrate vector DBs, embeddings, RAG, and cloud MLOps, drive automation/APIs, mentor engineers, set KPIs, and ensure observability, ethical AI, and production readiness.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.