Top Remote Machine Learning Jobs in Washington, DC

The Senior Machine Learning Engineer will enhance fraud detection capabilities through ML technologies, improve model performance, and lead high-impact ML projects from experimentation to production.

As a Product Manager, you'll transform data into opportunities, manage technical product development, and foster cross-functional collaboration for philanthropic initiatives.

Lead AI and engineering efficiency initiatives, integrating cutting-edge technologies into engineering processes, while promoting innovation and continuous improvement.

The role involves optimizing training systems for machine learning, improving performance, and developing high-performance GPU kernels for distributed training.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The Staff Machine Learning Engineer will define and build ML capabilities, design production systems, and lead ML strategy in a high-growth AI cybersecurity company.

The role involves defining and building ML capabilities, creating production systems, and managing data strategy while collaborating with engineers and leading an ML team.

The VP AI/Machine Learning will define and implement machine learning capabilities in a high-growth cybersecurity company, focusing on strategy, infrastructure, and building production systems. The role involves defining ML applications, data strategy, and mentoring an ML team.

The role involves defining and building the company's machine learning capabilities, designing production ML systems, owning data strategy, and partnering with engineers. Requires experience in ML system production and software engineering fundamentals.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

As a Senior Machine Learning Engineer, you'll develop and optimize ML systems, implement pipelines, and collaborate with cross-functional teams to enhance Yahoo's data capabilities.

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The Senior Machine Learning Operations Engineer will build and operationalize the ML Ops platform to deploy and monitor machine learning models, focusing on infrastructure, automation, and integrating ML workloads within the AWS-native architecture.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

As a Staff Machine Learning Engineer, you will design and evaluate ML models, optimize performance, and work with stakeholders to deliver AI solutions.