Top Senior Machine Learning Jobs in Richmond, VA

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.

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 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.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Seeking Applied Scientist to build scalable AI systems for estate planning, focusing on production-grade applications and document understanding using advanced AI models.

As a Senior Machine Learning Engineer, develop LLM evaluation frameworks and agentic AI workflows to extract insights from conversations and optimize customer experiences.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

The Machine Learning Engineer will design, build, and deploy ML models for data-driven products, collaborating with teams to optimize pipelines and improve performance.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves designing and maintaining backend systems for ML applications, working closely with cross-functional teams, and optimizing AWS services.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

Lead efforts in building and maintaining ML platforms, improve metrics pipelines, and manage data collection for perception systems. Collaborate with cross-functional teams and ensure workflow reproducibility and traceability.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The Senior Machine Learning Engineer at SmarterDx will deploy, maintain, and optimize machine learning models, collaborating across disciplines to integrate these solutions and improve clinical AI outcomes.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.