Top Machine Learning Jobs in Hampton, VA

As Engineering Manager for the Marketplace team, lead full-stack engineers, drive strategic vision, manage team processes, and enhance user experience using AI and ML innovations.

The Customer Success Manager will manage post-sales relationships, drive customer engagement and ROI, and advocate for client needs within the Buzz Solutions platform.

The role involves leading a team to manage data strategies and analytics for Netflix Games, requiring expertise in data science, business analytics, and team management.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Product Manager will lead the development of data-driven product capabilities at Axuall, ensuring features are delivered on time and meet customer needs through collaboration with various teams.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

The Senior Credit Risk Manager will oversee credit analysis, experimentation design, performance monitoring, and strategic decision support in the U.S. loans business.

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.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

As a Senior Machine Learning Engineer, you'll develop models for risk identification, collaborate cross-functionally, and deploy ML solutions, ensuring performance monitoring and continuous improvement.

Lead the vision, strategy, and execution of the machine learning platform at Flex, focusing on compliance, customer success, and internal operations. Build and mentor a team of ML engineers and data scientists to deliver scalable ML systems.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

The Research Scientist will conduct studies on natural language processing and machine learning, transition models to production, conduct experiments, publish research, and create new models to enhance products.

The Engagement Principal is responsible for the deployment of Aera solutions, managing client relationships, project delivery, and contributing to sales cycles, ensuring successful implementation and value delivery.

The Marketing Manager will lead strategic campaigns, manage content, collaborate with teams, analyze performance, and stay ahead of industry trends to drive brand awareness and customer engagement.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.

The role involves defining AI strategy for the AECO industry, prioritizing AI use cases, and guiding AI initiatives to align with Autodesk's portfolio.

As a Machine Learning Engineer, support innovation by training, testing, deploying, and maintaining ML models for mission-critical solutions in the defense technology sector.

Develop and deploy AI-driven text-to-speech solutions, ensuring production reliability and optimizing performance, collaborating with engineers and researchers.

As a Software Engineer at Speechify, you will work with machine learning teams to enhance AI Voice functionalities, manage deployments, and improve model efficiency.

The Director of Product Engineering leads the product engineering organization, overseeing technical direction, talent management, engineering excellence, and collaboration across teams to deliver secure, reliable digital products.