Top Machine Learning Jobs in Richmond, VA

The ML Administrator will manage machine learning model governance, optimize ML infrastructure, and validate AI/ML pipelines to support DoD projects.

The Machine Learning Engineer II will enhance ML capabilities for autonomous vehicles, train and optimize models, and ensure high performance through collaboration with cross-functional teams.

The Senior Product Manager will develop AI-driven capabilities for SurveyMonkey's platform, collaborating with engineering and data science teams to enhance user interaction and feedback collection.

Develop and deploy advanced ML solutions for OCR and NLP, optimizing models for performance and integrating them into production workflows while collaborating with cross-functional teams.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

As an Applied Machine Learning Platform Engineer, you'll design and maintain training infrastructure, manage distributed pipelines, and optimize data workflows for machine learning models.

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.

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.

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

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

The AI/ML Architect will define scalable architectures, guide teams on MLOps, advise clients on AI solutions, and ensure ethical AI practices.

The role involves developing and optimizing machine learning systems for voice experiences, focusing on speech recognition and language understanding. Responsibilities include training models, ensuring performance metrics, and collaborating with cross-functional teams for successful deployment.

The Senior Machine Learning Engineer designs and deploys scalable ML solutions, oversees model lifecycle management, enhances data integration, and ensures compliance with regulations.

As a Specialist Solutions Architect, you'll design ML & AI applications on Databricks, guide customers, provide technical support, and collaborate with teams to influence product strategy.

The Lead Machine Learning Engineer will design and evaluate models for autonomous driving systems, mentor junior engineers, and utilize large datasets to improve ML capabilities at May Mobility.

Lead and grow an AI/ML team, define strategic roadmap, prioritize and deliver scalable ML solutions on Azure, manage budgets and people, ensure best practices, and collaborate cross-functionally while supporting production and on-call incident response.

The MLOps Engineer will design and maintain the machine learning operations infrastructure, optimize cloud services, and build CI/CD pipelines to support AI products for underground infrastructure management.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

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

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

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.

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

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.

As a Senior/Staff ML Systems Engineer at Quilter, you'll design and maintain ML infrastructure for automated PCB component placement, manage data pipelines, and lead systems design reviews while ensuring project efficiency and reliability within a fully distributed team.

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