Top Machine Learning Jobs in Richmond, VA

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead technical direction on projects, mentor engineering teams, and build scheduling tools and forecasting interfaces for support agents. Collaborate with product and design teams to convert vague problems into technical solutions.

Lead a team to develop Dropbox's AI product, Dash. Focus on driving product revenue, operational agility, and mentoring team members. Utilize ML techniques and data-driven insights for decision making.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

The role involves managing AI/ML products at Velocity Black, collaborating with stakeholders, optimizing concierge services, and driving innovation. Candidates should have experience in product management and a passion for AI/ML technologies.

As a Senior Business Analyst on the AI/ML team at Velocity Black, you will analyze data, support model governance, and collaborate with cross-functional teams to enhance product offerings through AI and ML tools.

Lead a team of ML and DevOps engineers to build infrastructure for the ML ecosystem, including tools for experimentation and deployment. Manage a distributed team while enhancing capabilities in ML system operation and analytics production.

Lead the development of AI-powered systems at Capital One, collaborating with cross-functional teams to deliver innovative machine learning solutions and optimize data pipelines.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

Responsible for designing and deploying large-scale machine learning systems, optimizing performance, collaborating with cross-functional teams, and ensuring safe and responsible AI practices.

The Staff Full Stack Engineer will enhance machine learning workflows at Cruise by developing UX experiences, backend integrations, and overseeing system architecture and performance metrics.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

The P&C Actuary will assess financial risks in insurance, assist in regulatory consulting, and ensure compliance while enhancing client relationships and business development.

The BSS Solution Architect will define customer solutions, manage end-to-end architecture, ensure implementation integrity, and contribute to sales and project delivery.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

As a Principal Product Manager, you will manage cross-portfolio initiatives, collaborate with Data and Engineering teams, and ensure product alignment with customer needs.

The VP of FP&A will lead Pacvue's FP&A function, partner with CFO, build a high-performing team, and support strategic growth initiatives.

Lead the technical vision for deep learning architecture in therapeutic discovery. Mentor a team and collaborate across functions to implement innovative machine learning models.

The Head of Disputes & AI Operations will lead Casap's dispute strategy, leverage AI to optimize processes, and ensure customer success while overseeing a high-impact team.

The Sales Engineer will serve as a technical lead, guiding clients on advanced data integration and analytics solutions in healthcare, impacting revenue and client engagement.

The VP of Business Development will lead sales growth strategies, manage relationships, and build the BD team to drive significant revenue increases.

The Machine Learning Scientist will develop models and systems for content metadata and discovery at Netflix, collaborating with teams to operationalize AI solutions. The role requires significant experience and collaboration with stakeholders.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.