Top Remote Senior Level Machine Learning Engineer Jobs in Washington DC,

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

The Principal Software Engineer II will build and maintain machine learning components in Elasticsearch, collaborating with teams, writing scalable code, and owning projects from design to implementation.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The Senior Machine Learning Engineer will design and implement detection systems to improve email security, lead project execution, and mentor junior engineers.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

Lead the architecture, development, and management of machine learning systems for personalized decision-making, ensuring reliability and explainability in real-time contexts.

Design, develop, and deploy production machine learning models to improve decisioning for consumer lending. Partner with business and technical teams to develop data sources, improve modeling methodology, manage models in production, and mentor others while practicing strong software engineering and MLOps practices.